Therapeutic bacterial composition

ABSTRACT

The invention relates to bacterial compositions useful in the treatment of cancer. In particular, the compositions can be used as a co-therapy with an immune checkpoint therapy. The invention also relates to methods for identifying a subject that will respond to therapy with an immune checkpoint inhibitor comprising determining the abundance of bacteria in a biological sample from said subject.

STATEMENT REGARDING ELECTRONIC FILING OF A SEQUENCE LISTING

A Sequence Listing in ASCII text format, submitted under 37 C.F.R. §1.821, entitled 1553-10 Sequence_ST25.txt, 62,388 bytes in size,generated on May 18, 2021 and filed via EFS-Web, is provided in lieu ofa paper copy. This Sequence Listing is hereby incorporated herein byreference into the specification for its disclosure.

INTRODUCTION

Immune suppression and evasion by malignant cancer cells is known as oneof the hallmarks of cancer. A number of co-inhibitory receptors andtheir ligands, known as immune checkpoints, contribute to this process.Immune checkpoint inhibitor cancer immunotherapies have beentransformational in cancer management in that they can lead to long-termremission and they can be effective across many cancers. Among thesecheckpoints are programmed cell death 1 (PD-1), PD-L1 and CTLA-4. Theintroduction of PD-1 inhibitors into clinical practice has had arevolutionary effect on cancer treatment, but consistent responses andfavourable long-term outcomes are only observed in a fraction ofpatients. The majority of patients do not respond to therapy. Thehighest proportion is for melanoma (reaching 40%), but it is much lowerfor the other cancers. Moreover, a significant number of patientsdevelop immune-related adverse events and have to stop therapy.

Accordingly, there is a need for (a) biomarkers to predict response toimmune checkpoint inhibitors and (b) approaches to increase theproportion of cancer patients that respond to therapy.

PD-1 (UniProt Accession No. 015116, GenBank Accession No. U6488) proteinis encoded by the PDCD1 gene and expressed as a 55 kDa type Itransmembrane protein (Agata 1996 Int Immunol 8(5):785-72). PD-1 is animmunoglobulin superfamily member (Ishkda 1992 EMBO 11(11):3887-95) andit is an inhibitory member of the extended CD28/CTLA-4 family of T cellregulators. Other members of this family include CD28, CTLA-4, ICOS andBTLA. PD-1 exists as a monomer, lacking the unpaired cysteine residuecharacteristic of other CD28 family members (Zhang 2004 Immunity20:337-47). Its cytoplasmic domain contains an immunoreceptortyrosine-based inhibitory motif (ITIM) and an immunoreceptortyrosine-based switch motif (ITSM) that are phosphorylated during signaltransduction (Riley 2009 Immunol Rev 229(1):114-25).

PD-1 is expressed on B cells, T cells, and monocytes (Agata 1996). Therole of PD-1 in maintaining immunologic self-tolerance was demonstratedin PDCD1−/− mice, which develop autoimmune disorders (Nishimura 1999Immunity 11:141-51, Nishimura 2001 Science 291(5502):319-22). The PD-1pathway therefore regulates antigen responses, balancing autoimmunityand tolerance.

There are two ligands for PD-1 that mediate its regulatory function.PD-L1 (B7-H1) is normally expressed on dendritic cells, macrophages,resting B cells, bone marrow-derived mast cells and T cells as well asnon-hematopoietic cell lineages (reviewed in Francisco 2010 Immunol Rev236:219-42). PD-L2 (B7-DC) is largely expressed on dendritic cells andmacrophages (Tseng 2001 J Exp Med 193(7):839-45). Ligand expression isinfluenced by local mediators and can be upregulated by inflammatorycytokines.

PD-1 is known as an immunoinhibitory protein that negatively regulatesTCR signals. The interaction between PD-1 and PD-L1 can act as an immunecheckpoint, which can lead to, e.g., a decrease in tumour infiltratinglymphocytes, a decrease in T-cell receptor mediated proliferation,and/or immune evasion by cancerous cells. Immune suppression can bereversed by inhibiting the local interaction of PD-1 with PD-L1 orPD-L2; the effect is additive when the interaction of PD-1 with bothPD-L1 and PD-L2 is blocked.

The PD-1 pathway can be exploited in cancer or infection, wherebytumours or viruses can evade effective immune recognition and T cellsdemonstrate an ‘exhausted’ phenotype.

Disruption of the PD-1:PD-L1 interaction enhances T cell activity.Inhibitory anti-PD-1 monoclonal antibodies demonstrate blockade of theinteraction between PD-1 and its ligands (Wang 2014 Cancer Immunol Res2(9):846-56). T cell function in vitro can be enhanced by PD-1 blockade,as demonstrated by improved proliferation and cytokine responses inmixed lymphocyte reactions of T cells and dendritic cells. Cytotoxic TLymphocytes (CTLs) derived from melanoma patients have also been shownto be enhanced by PD-1 blockade in vitro using the antibody nivolumab,and can become resistant to suppression by regulatory T cells (Wang 2009Int Immunol 21(9):1065-1077). This antibody has been shown to beefficacious in melanoma and in non-small-cell lung carcinoma (NSCLC)patients. Another PD-1 blocking antibody, pembrolizumab, demonstratesresponses in NSCLC patients refractory to CTLA-4 blockade. Nivolumab andpembrolizumab both functionally block the interaction of human PD-1 withits ligands.

The gut microbiome of cancer patients is a major driver of response toimmune checkpoint therapy.

Previous studies have analysed clinical datasets to identify gutmicrobiota associated with treatment efficacy (Frankel Neoplasla (2017)19:848; Gopalakrishnan Science (2018) 359:97; Matson Science (2018)359:104; Routy Science (2018) 359:91). However, the major challenge inthe field has been that the microbiome signatures identified in theindependent studies are very different. The published studies vary inresponse criteria and cancer indication, but also factors that are knownto impact microbiome analysis such as sample collection, storage andprocessing and geographical location. Therefore, it has been difficultto understand what the true signature is amongst the inter-study noise.

Thus, there is a need to provide efficacious treatments of cancer aswell as biomarkers that are predictive for response to treatment and thepresent invention is aimed at addressing this need.

SUMMARY OF THE INVENTION

The invention is based on the finding that the gut microbiome insubjects that respond to treatment with an immune checkpoint inhibitoris different to the gut microbiome in subjects that do not respond totreatment with the immune checkpoint inhibitor, and that the gutmicrobiome may therefore be employed either as a diagnostic for immunecheckpoint inhibitor treatment or as the source of a therapy.

The invention is therefore aimed at a number of aspects, including, butnot limited to the following:

-   -   A composition comprising certain bacteria as defined herein        which have been identified in patients who respond to treatment        with an immune checkpoint inhibitor and which can be used as a        treatment of disease, including treatment of cancer, an        infectious disease or use as a vaccine adjuvant;    -   A co-therapy comprising a composition having certain bacteria as        defined herein and an immune checkpoint inhibitor treatment and    -   Provision of certain bacteria as defined herein as a diagnostic        for immune checkpoint inhibitor treatment to identify patients        that benefit from immune checkpoint inhibitor treatment and also        to identify patients which may receive bacterial or other        therapy, e.g. before administration of the checkpoint inhibitor        therapy.

These aspects as well as other related aspects of the invention andembodiments are further described herein.

The inventors have identified a microbiome biomarker signatureassociated with and highly predictive of response to treatment with animmune checkpoint inhibitor. This is of great significance in the field,providing the basis for the following: a predictive biomarker forcheckpoint inhibitor therapy; a live bacterial therapeutic (LBT)therapy; a live bacterial therapeutic co-therapy with an immunecheckpoint inhibitor, for example anti-PD-1, anti-PD-L1 or anti-CTLA-4drugs for the treatment of cancer, to increase the proportion ofpatients responding to checkpoint inhibitors. In particular, theinventors have identified a number of bacterial species present in thegut microbiome that exhibit modulated abundance indicative of a responseto treatment with an immune checkpoint inhibitor. Detecting modulatedabundance of these bacteria may therefore be employed to discriminateresponders to checkpoint inhibitor therapy from non-responders. Inaddition, the administration of such live bacteria as a medicine ispredicted to convert patients not responding to checkpoint inhibitors toresponders.

The bacteria identified and described herein may be employedindividually to determine response and/or provide treatment, orcombinations of the bacteria may be provided to increase thediscriminatory power of the diagnostic method and provide non-invasivemethods of diagnosis for response versus non-response as well as methodsof treatment.

The inventors have identified specific gut bacteria associated withcheckpoint inhibitor response. The invention thus provides gut bacteriathat can be used to modulate the microbiome to improve the therapeuticresponse to immune checkpoint inhibitors patients, for example cancerpatients. Studies in the present disclosure used a cohort of patientswith melanoma undergoing therapy with anti-PD-1 drugs or combinationtherapy with anti-PD-1 plus anti-CTLA-4 drugs. Gut microbiome samplestaken prior to immune checkpoint therapy were characterized in thesepatients via metagenomic whole genome shotgun sequencing. Significantdifferences were observed in the composition of the gut microbiome inresponders versus non-responders to immune checkpoint blockade therapy(e.g., to PD-1-based therapy), with an increase or decrease in abundanceof specific bacteria in the gut microbiome of responders versusnon-responders pre-treatment. In particular, the bacteria as describedherein were found to be more abundant in responders. Therefore, thesebacteria and subsets thereof find use in a composition which can beemployed for the treatment of disease, including cancer, either alone orin combination with an immune checkpoint inhibitor treatment.Furthermore, these bacteria can be used as biomarkers, i.e. as adiagnostic to distinguish responders to checkpoint inhibitor, e.g. PD-1inhibitor, therapy from non-responders for immune checkpoint inhibitortreatment.

The present studies show that patients with a “favourable” gutmicrobiome (with modulated, e.g. high relative abundance of one or moreof bacteria as described herein) have enhanced anti-tumour immuneresponses. In contrast, patients with an “unfavourable” gut microbiome(with low relative abundance of the species B1-B15 as defined herein)have impaired anti-tumour immune responses. These findings highlight thepotential for parallel modulation of the gut microbiome to significantlyenhance checkpoint blockade treatment efficacy. Based on these findings,methods of disease management, e.g. cancer treatment and diagnosis areprovided herein. Also provided herein are methods to use thecompositions described herein as predictive biomarker compositions toidentify patients who will have a favourable response to immunecheckpoint blockade. Moreover, the compositions described herein haveimmunostimulatory properties. Therefore, treatment of disease is notlimited to cancer, but the compositions provides treatment of otherdiseases, e.g. diseases that benefit form immunostimulatory treatment,e.g. non-cancer immunotherapies.

In a first aspect, the invention thus relates to a compositioncomprising one or more bacterial isolate, in particular a bacterialpopulation, belonging to one or more bacterial species selected fromTable 1. Thus, the invention relates to a composition comprising abacterium selected from one or more bacteria selected from Table 1.Specifically, the invention thus relates to a composition comprising oneor more bacterial isolate having a 16SrDNA selected from SEQ ID. Nos 1to 15.

The composition may comprise or consists of 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14 or 15 isolated bacteria. These are different bacteriaselected from different species, that is bacteria having a 16SrDNA ofselected from SEQ ID. Nos 1 to 29 or a sequence having at least 95%,97%, 98% 98.7%, 99% or 100% sequence identity with a nucleic acidsequence selected from SEQ ID. Nos 1 to 29, e.g. selected from SEQ ID.Nos 1 to 15 or a sequence having at least 95%, 97%, 98% 98.7% or 99%sequence identity with a nucleic acid sequence selected from SEQ ID. Nos1 to 15.

In one embodiment, the composition thus comprises or consists ofisolated bacteria selected from at least 2, 3, 4, 5, 6, 7, 5, 9, 10, 11,12, 13, 14 or 15 bacterial species wherein the bacteria comprise a 16SrDNA sequence selected from SEQ ID. Nos 1 to 29, e.g. 1 to 15, or asequence having at least 95%, 97%, 98% 98.7%, 99% or 100% sequenceidentity with a nucleic acid sequence selected from SEQ ID. Nos 1 to 15.

In one embodiment, the composition comprises or consists of isolatedbacteria selected from at least two species wherein the bacteria fromthe first species comprise a 16S rDNA sequence having least 95%, 97%,98%, 98.7%, 99% or 100% sequence identity with a nucleic acid sequenceaccording to SEQ ID NO: 1, and the bacteria from the second speciescomprise a 16S rDNA sequence having at least 95%, 97%, 98%, 98.7%, 99%or 100% sequence identity with a nucleic acid sequence according to SEQID NO: 2.

In one embodiment, the composition comprises or consists of isolatedbacteria selected from at least 9 species wherein the bacteria comprisea 16S rDNA sequence selected from SEQ ID. Nos 1 to 29, e.g. 1 to 15 or asequence having at least 95%, 97%, 98%, 98.7%, 99% or 100% sequenceidentity with a sequence selected from SEQ ID. Nos 1 to 29, e.g. 1 to15. In one embodiment, the 9 species include bacteria comprising a 16SrDNA sequence according to SEQ ID NO: 1, or a sequence having at least95%, 97%, 98% 98.7%, 99% or 100% sequence identity thereto and bacteriacomprising a 16S rDNA sequence according to SEQ ID NO: 2 or a sequencehaving at least 95%, 97%, 98%, 98.7%, 99% or 100% sequence identitythereto.

In another aspect, the invention relates to a pharmaceutical compositionas described herein, a pharmaceutical carrier and optionally an immunecheckpoint inhibitor.

In another aspect, the invention relates to a composition as describedherein for use in the treatment of disease, such as particular cancer oran infectious disease. The composition can also be used as a vaccineadjuvant. This is used to enhance vaccine response and administrationmay be together with the vaccine.

In another aspect, the invention relates to a composition as describedherein in increasing efficacy of an anti-cancer treatment with an immunecheckpoint inhibitor.

In another aspect, the invention relates to a method for treating cancercomprising modulating the level/abundance of one or more bacteriaselected from those of Table 1 in a subject.

In another aspect, the invention relates to a kit comprising acomposition as described herein and optionally an anti-cancer treatmentthat includes an immune checkpoint inhibitor.

In another aspect, the invention relates to a method for identifying asubject that will respond to therapy with an immune checkpoint inhibitorcomprising determining the abundance of one or more bacteria selectedfrom those of Table 1 in a biological sample from said subject thatcomprises gut intestinal flora wherein an increase in the abundance ofone or more of bacteria selected from those of Table 1 is indicativethat the subject will respond to therapy with an immune checkpointinhibitor.

In another aspect, the invention relates to a use of a bacteriumselected from one or more bacteria selected from those of Table 1 inidentifying a patient that win respond to therapy with an immunecheckpoint inhibitor.

In another aspect, the invention relates to a kit comprising;

-   -   a sealable container configured to receive a biological sample;    -   polynucleotide primers for amplifying a 16S rDNA polynucleotide        sequence from at least one gut associated bacterium to form an        amplified 16S rDNA polynucleotide sequence, wherein the        amplified 16S rDNA sequence has at least 95%, 97%, 98%, 98.7%,        99% or 100% sequence identity to a polynucleotide sequence        selected from SEQ ID NOs 1 to SEQ ID NO 29; e.g. 1 to 15, a        detecting reagent to detect the amplified 16S rDNA sequence; and        instructions for use.

In another aspect, the invention relates to a food product or a vaccineco-therapy to boost vaccine response comprising the composition asdescribed herein.

In another aspect, the invention relates to a method for identifying afaecal donor, e.g. for treatment of cancer, comprising assessing afaecal sample of a subject for the presence of one or more bacteriaselected from Table 1 and identifying the faecal donor based on thepresence and/or abundance of one or more bacteria selected from Table 1.

In another aspect, the invention relates to a use of one or morebacteria selected from Table 1 in a method for identifying a donor forFMT therapy, e.g. for treatment of cancer.

In another aspect, the invention relates to a method for treating afaecal transplant prior to administration to a subject comprisingsupplementing the faecal transplant with one or more isolated bacteriaselected from Table 1.

In another aspect, the invention relates to a method forscreening/identifying a faecal donor comprising assessing a faecalsample of a subject for the presence of one or more bacteria associatedwith response to cancer; and identifying the faecal donor based on thepresence and/or abundance of one or more bacteria.

DESCRIPTION OF FIGURES

FIG. 1. A) All 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of bacteria in a defined signature. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 91.16%. xaxis is group. B) As A except each study is considered separately.frankel accuracy 84.62%; gajewski accuracy 89.74%; melresist accuracy93.18%; wargo accuracy 100%. X axis is group. C) Receiver OperatingCharacteristic (ROC) curve of the combined melanoma dataset showingFalse Positive Rate as a function of True Positive Rate based on machinelearning predictions based the same microbiome signature. AUC=0.98. Xaxis is 1-specificity, y axis is sensitivity. D) As C but each study isconsidered separately. Random forest out-of-bag error was used toprevent overoptimistic performance and improve generalizability. AUCfrankel 0.958; AUC gajewski 0.978; AUC melresist 0.983; AUC wargo 1. Xaxis is 1-specificity, y axis is sensitivity.

FIG. 2. A) All 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of the 15 bacteria in consortium 1. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 77.55%.B) As A except each study is considered separately. frankel accuracy79.49%; gajewski accuracy 66.67%; melresist accuracy 81.82%; wargoaccuracy 84%. C) Receiver Operating Characteristic (ROC) curve of thecombined melanoma dataset showing False Positive Rate as a function ofTrue Positive Rate based on machine learning predictions based onconsortium 1. AUC=0.8. D) As C but each study is considered separately.Random forest out-of-bag error was used to prevent overoptimisticperformance and improve generalizability. AUC frankel 0.867; AUCgajewski 0.725; AUC melresist 0.879; AUC wargo 0.773.

FIG. 3. A) All 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of the 9 bacteria in consortium 2. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 74.15%.B) As A except each study is considered separately. frankel accuracy76.92%; gajewski accuracy 69.23%; melresist accuracy 75%; wargo accuracy76%. C) Receiver Operating Characteristic (ROC) curve of the combinedmelanoma dataset showing False Positive Rate as a function of TruePositive Rate based on machine learning predictions based on consortium2. AUC=0.75. D) As C but each study is considered separately. Randomforest out-of-bag error was used to prevent overoptimistic performanceand improve generalizability. AUC frankel 0.831; AUC gajewski 0.676; AUCmelresist 0.788; AUC wargo 0.734.

FIG. 4. A) All 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of the 12 bacteria in consortium 3. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 74.15%.B) As A except each study is considered separately. frankel accuracy76.92%; gajewski accuracy 66.67%; melresist accuracy 81.82%; wargoaccuracy 68%. C) Receiver Operating Characteristic (ROC) curve of thecombined melanoma dataset showing False Positive Rate as a function ofTrue Positive Rate based on machine learning predictions based onconsortium 3. AUC=0.773. D) As C but each study is consideredseparately. Random forest out-of-bag error was used to preventoveroptimistic performance and improve generalizability. AUC frankel0.844; AUC gajewski 0.685; AUC melresist 0.862; AUC wargo 0.76.

FIG. 5. A) All 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of the 9 bacteria in consortium 4. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 71.43%.B) As A except each study is considered separately. frankel accuracy76.92%; gajewski accuracy 64.1%; meiresist accuracy 77.27%; wargoaccuracy 64%. C) Receiver Operating Characteristic (ROC) curve of thecombined melanoma dataset showing False Positive Rate as a function ofTrue Positive Rate based on machine learning predictions based onconsortium 4. AUC=0.737. D) As C but each study is consideredseparately. Random forest out-of-bag error was used to preventoveroptimistic performance and improve generalizability. AUC frankel0.781; AUC gajewski 0.667; AUC melresist 0.791; AUC wargo 0.708.

FIG. 6. A) All 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of the 9 bacteria in consortium 5. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 68.71%.B) As A except each study is considered separately. frankel accuracy71.79%; gajewski accuracy 58.97%; meiresist accuracy 70.45%; wargoaccuracy 76%. C) Receiver Operating Characteristic (ROC) curve of thecombined melanoma dataset showing False Positive Rate as a function ofTrue Positive Rate based on machine learning predictions based onconsortium 3. AUC=0.69. D) As C but each study is considered separately.Random forest out-of-bag error was used to prevent overoptimisticperformance and improve generalizability. AUC frankel 0.75; AUC gajewski0.596; AUC melresist 0.766; AUC wargo 0.675.

FIG. 7. A) AN 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of the 9 bacteria in consortium 6. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 69.39%.B) As A except each study is considered separately. frankel accuracy69.23%; gajewski accuracy 58.97%; melresist accuracy 77.27%; wargoaccuracy 72%. C) Receiver Operating Characteristic (ROC) curve of thecombined melanoma dataset showing False Positive Rate as a function ofTrue Positive Rate based on machine learning predictions based onconsortium 3. AUC=0.71. D) As C but each study is considered separately.Random forest out-of-bag error was used to prevent overoptimisticperformance and improve generalizability. AUC frankel 0.767; AUCgajewski 0.577; AUC melresist 0.81; AUC wargo 0.708.

FIG. 8. Receiver Operating Characteristic (ROC) curve of a NSCLC cohortshowing False Positive Rate as a function of True Positive Rate based onmachine learning predictions based on consortium 1. NSCLC dataset ismetagenomic sequence from Routy and Zitvogel et al (2018 Science359:91-97) classified using the Microbiotica high-precision platform.Random forest out-of-bag error was used to prevent overoptimisticperformance and improve generalizability. AUC=0.744.

FIG. 9. Isolated bacteria induce dendritic cell maturation and cytokineproduction. The ability of the isolated bacteria to activate dendriticcells (DCs) was determined by co-culturing with human monocyte-derivedDendritic cells in anaerobic conditions at multiplicity of infection(MOI) of approximately 10:1. Subsequent maturation of the dendriticcells was determined by expression levels of the maturation markers CD86(A) and CD83 (B) as determined by flow cytometry. Data is displayed asfold change of mean fluorescence intensity (MFI), compared to the LPScontrol to normalise across different donors and experiments. The DCexpression of CD86 (C) and CD83 (D) following treatment with consortium5 (MOI of approximately 10:1) was similarly determined by flowcytometry. The MFIs of those markers following stimulation withconsortium 5 are displayed in white bars. The DC expression of CD86 (E)and CD83 (F) following treatment with consortia 6, 7, 8 and 9 wasdetermined by flow cytometry. The MFIs of those markers are displayed inwhite bars. (G) IL-12 and IL-10 production by DCs following treatmentwith isolated bacteria alone (MOI of approximately 10:1) or as consortia5 and 6 (MOI of approximately 10:1) were determined by ELISA. MOI 10 N=5(5 donors in 5 independent experiments). Data are displayed as ratio ofIL-12 to IL-10. LPS (10 ng/ml), Poly I:C (20 μg/ml) and Salmonellatyphimurium (MOI of approximately 10:1) are strong inducers of DCactivation and used as positive controls for all assays (grey bars).Unstimulated or immature (Imm) DCs are shown for comparison (grey bars).Results are the mean±SEM of 5 (A and B), 2 (C, D, E and F) and 3 (G)independent experiments.

FIG. 10. Dendritic cells treated with isolated bacteria activateCytotoxic CD8+ T Lymphocytes (CTLs). Following co-culture with isolatedbacteria or control stimuli as in FIG. 9, human monocyte-derived DCswere washed and co-cultured with purified allogenic CD8+ T cells for 6days. CTL activation was determined by analysing the expression ofGranzyme B (A). IFN-γ (B) and Perforin (C) using intracellular stainingand flow cytometry. Data is displayed as fold change of the percentageof positive cells, compared to the LPS control to normalise acrossdifferent donors and experiments. LPS (10 ng/ml), Poly I:C (20 μg/ml)and Salmonella typhimurium (MOI of approximately 10:1) are stronginducers of DC activation and used as positive controls for all assays(grey bars). Unstimulated or immature (Imm) DCs are shown for comparison(grey bars). Results are the mean±SEM of 7 donors in 4 independentexperiments.

FIG. 11. Dendritic cells treated with consortia 6, 7, 8 and 9 activateCytotoxic CD8+ T Lymphocytes (CTLs). Following co-culture with consortia6, 7, 8 and 9 or control stimuli as in FIG. 9, human monocyte-derivedDCs were washed and co-cultured with purified allogenic CD8+ T cells for6 days. CTL activation was determined by analysing the expression ofGranzyme B (A), IFN-γ (B) and Perforin (C) using intracellular stainingand flow cytometry. Data is displayed as the percentage of positivecells. LPS (10 ng/ml), Poly I:C (20 μg/ml) and Salmonella typhimurium(MOI of approximately 10:1) are strong inducers of DC activation andused as positive controls for all assays (grey bars). Unstimulated orimmature (Imm) DCs are shown for comparison (grey bars). Results are themean±SEM of a duplicate of a single representative experiment.

FIG. 12. Dendritic cells treated with consortium 5 activate CytotoxicCD8+ T Lymphocytes (CTLs). Following co-culture with consortium 5 orcontrol stimuli as in FIG. 11, human monocyte-derived DCs were washedand co-cultured with purified allogenic CD8+ T cells for 6 days. CTLactivation was determined by analysing the expression of Granzyme B (A),IFN-γ (B) and Perforin (C) using intracellular staining and flowcytometry. Data is displayed as the percentage of positive cells. LPS(10 ng/ml), Poly I:C (20 μg/ml) and Salmonella typhimurium (MOI ofapproximately 10:1) are strong inducers of DC activation and used aspositive controls for all assays (grey bars). Unstimulated or immature(Imm) DCs are shown for comparison (grey bars). Results are the mean±SEMof a duplicate of a single representative experiment.

FIG. 13. Isolated bacteria and consortia 6, 7, 8 and 9 endow the inducedCTLs with tumor killing capacity. CD8+ T cells primed bybacteria/consortia-treated DCs (as in FIGS. 10 and 11) were assessed fortheir capacity to kill SKOV-3 cells. Cytolysis is determined bymeasuring the decreasing electric impedance of the SKOV-3 cells. Data isdisplayed as the percentage of cytolysis of SKOV-3 cells, 72 hoursfollowing co-culture with CD8+ T cells. LPS (10 ng/ml), Poly I:C (20μg/ml) and Salmonella typhimurium (MOI of approximately 10:1) are stronginducers of DC activation and used as positive controls for all assays(grey bars). Unstimulated or immature (Imm) DCs are shown for comparison(grey bars). Results are the mean±SEM of 3 independent experiments.

FIG. 14. Consortium 5 and Blautia sp. endow the induced CTLs with tumorkilling capacity. CD8+ T cells primed by consortium 5- or Blautiasp.-treated DCs (as in FIG. 12) were assessed for their capacity to killSKOV-3 cells. Cytolysis is determined by measuring the decreasingelectric impedance of the SKOV-3 cells. Data is displayed as thepercentage of cytolysis of SKOV-3 cells, 72 hours following co-culturewith CD8+ T cells. LPS (10 ng/ml), Poly I:C (20 μg/ml) and Salmonellatyphimurium (MOI of approximately 10:1) are strong inducers of DCactivation and used as positive controls for all assays (grey bars).Unstimulated or immature (Imm) DCs are shown for comparison (grey bars).Results are the mean±SEM of a duplicate of a single representativeexperiment.

FIG. 15. Isolated bacteria possess a variable capacity to induce IFN-αproduction by plasmacytoid dendritic cells. IFN-α production byplasmacytoid dendritic cells (pDCs) was determined by ELISA following anovernight incubation with heat-killed bacteria (moimoi of approximately10:1). 10 ng/ml IL-3 and 10 μg/ml CpG (grey bars) were taken along as anegative and positive controls, respectively. Results are the mean±SEMof 3 donors in 2 independent experiments.

FIG. 16. In vivo efficacy in a murine cancer model Prior to tumourimplantation, SPF C57BL/8N female mice were administered antibiotics indrinking water (kanamycin (0.4 mg/ml), colistin (850 U/ml),metronidazole (0.215 mg/m), vancomycin (0.045 mg/ml), gentamycin (0.035mg/ml)) for 7 days (day −9 to day −2). Subsequently, mice werereconstituted with human donor stool from a melanoma patient (20 mg) byoral gavage on day −1. 5×10⁵ MCA-205 murine fibrosarcoma cells wereimplanted subcutaneously in the flank on day 0. Consortium 5 (n=8) andconsortium 6 (n=8) were administered by oral gavage twice weekly fromday −1 for 3 weeks (approximate total of 1×10⁹ CFU/dose) and compared toanimals treated with vehicle controls. Anti-PD-1 antibody (RMP1-14) wasadministered (10 mg/kg intraperitoneal) thrice weekly for 2 weeks fromday 6. Plots show tumour growth, as measured by volume, over time inresponse to vehicle control, anti-PD1 and Consortium 5 (A) or consortium6 (B). Data are mean±SEM tumour size, and representatives of at leastthree (A) and two (B) experiments.

FIG. 17. A) All 147 patients from the four melanoma studies were dividedinto responders and non-responders according to clinical outcome. Theprobability of not responding to immunotherapy was predicted from thebaseline faecal sample based on machine learning predictions that usedthe abundance of the 9 bacteria in consortium 10. A cut off of 0.5 wasused to determine the accuracy of the prediction. Accuracy was 75.51%.B) As A except each study is considered separately. frankel accuracy74.38%; gajewski accuracy 71.79%; melresist accuracy 77.27%; wargoaccuracy. C) Receiver Operating Characteristic (ROC) curve of thecombined melanoma dataset showing False Positive Rate as a function ofTrue Positive Rate based on machine learning predictions based onconsortium 3. AUC=0.81. D) As C but each study is considered separately.Random forest out-of-bag error was used to prevent overoptimisticperformance and improve generalizability. AUC frankel 0.85; AUC gajewski0.725; AUC melresist 0.826; AUC wargo 0.805.

In the figures, Con stands for consortium. Consortia are shown in Table3.

DETAILED DESCRIPTION

The present invention will now be further described. In the followingpassages, different aspects of the invention are defined in more detail.Each aspect so defined may be combined with any other aspect or aspectsunless clearly indicated to the contrary. In particular, any featureindicated as being preferred or advantageous may be combined with anyother feature or features indicated as being preferred or advantageous.

Generally, nomenclatures used in connection with, and techniques ofmicrobiology, cell and tissue culture, pathology, molecular biology,immunooncology, genetics and protein and nucleic acid chemistry andhybridization described herein are those well-known and commonly used inthe art. The methods and techniques of the present disclosure aregenerally performed according to conventional methods well-known in theart and as described in various general and more specific referencesthat are cited and discussed throughout the present specification unlessotherwise indicated. See, e.g., Green and Sambrook et al., MolecularCloning: A Laboratory Manual, 4th ed., Cold Spring Harbor LaboratoryPress, Cold Spring Harbor, N.Y. (2012).

The nomenclatures used in connection with, and the laboratory proceduresand techniques of analytical chemistry, microbiology, bioinformatics andmedicinal and pharmaceutical chemistry described herein are thosewell-known and commonly used in the art.

The invention relates to bacterial compositions each comprising orconsisting of one or more bacterial isolate from one or more species asdisclosed herein, e.g., a consortium of defined bacterial isolates.

The compositions have immunostimulatory properties and are thustherapeutic compositions useful in the treatment of disease. In someembodiments, the compositions are mixtures of bacterial isolatesselected from more than one species as identified in Table 1.

The compositions are not faecal microbiota transplants (FMT) and do notcontain faecal material, but contain defined mixtures of bacterialisolates free of faecal material. Therefore, preparations that contain adefined bacterial mixture are generally accepted to be a safer treatmentthan FMT. An advantage of the present composition is that it comprisesonly fully defined and characterised bacteria and no undefined orunwanted components, which may be present in donor stools, therebyallowing the therapeutic composition to be standardised and increasingsafety of the composition.

FMT relies on a stool sample from a human donor which is administereddirectly to the recipient, e.g. via colonoscopy, without bacteriapresent in the stool sample being isolated prior to the administrationof the FMT to the recipient. While FMT is widely used, there are somedisadvantages associated with FMT. The composition of the FMT materialis very donor dependent and therefore is inconsistent. Despite screeningof donors, it is difficult to determine the bacterial load of thesamples. Donors also have to be screened for pathogens and to assess therisk of colonization with drug-resistant bacteria. In certain aspectsdescribed below, the invention also relates to augmenting FMT therapywith one or more bacterial isolate from one or more species as disclosedherein and methods for screening/identifying a faecal donor.

The compositions as described herein include isolated bacteria. The term“isolated” refers to bacteria that are isolated from the naturalenvironment. The isolated bacteria, e.g. isolated bacterial strains, aresubstantially free of other cellular material, chemicals and/or faecalmaterial. Thus, as used herein, the term “isolated” bacteria refers tobacteria that have been separated from one or more undesired component,such as another bacterium or bacterial strain, one or more component ofa growth medium, and/or one or more component of a sample, such as afaecal sample. In some embodiments, the bacteria are substantiallyisolated from a source such that other components of the source are notdetected. As used herein, the term “species” refers to a taxonomicentity as conventionally defined by genomic sequence and/or phenotypiccharacteristics. A “strain” is a particular instance of a species thathas been isolated and purified according to conventional microbiologicaltechniques. It will be understood that the terms bacteria and bacterialisolates refer to a plurality of bacteria, that is a bacterialpopulation.

In one embodiment, the bacteria of the composition are metabolicallyinactive prior to administration. For example, the bacteria arelyophilsed. In one embodiment, the composition includes vegetativebacterial cells and does not include bacterial spores. In oneembodiment, the composition includes vegetative bacterial cells and/orbacterial spores. In one embodiment, the composition includes vegetativebacterial cells and does not include bacterial spores or issubstantially devoid of spores. In one embodiment, the compositionincludes fewer than about 0.5%, 1%, 2%, 3%, 4% or 5% spores.

The composition is preferably a live bacterial therapeutic,bacteriotherapy or a live biotherapeutic product. As described herein, alive bacterial product (also referred to as a bacterial composition,live bacterial consortium, mixture of bacteria or bacterial consortium)comprises one or more bacterial strain from one or more bacterialspecies as described herein. The term live bacterial therapy isinterchangeably used with bacteriotherapy herein and defines a therapyusing live bacteria to restore health or alleviate disease/diseasesymptoms or increase response to a therapy.

The bacterial compositions of the invention provide an immunostimulatoryeffect. In some embodiments, the bacterial composition induces orstimulates an immunotherapeutic effect, for example an anti-cancereffect (e.g., inhibition or cytotoxicity of cancer cells), whenadministered to the subject. In some embodiments, the bacterialcomposition induces or stimulates an immune response that provides ananti-cancer or other beneficial therapeutic effect when administered tothe subject as further explained herein.

As described herein, the composition may comprise one or more bacterialspecies selected from those listed in Table 1. The ability of thespecific bacteria or the combination of bacterial species of the livebacterial product to induce a beneficial effect, i.e. animmunostimulatory effect, such as an anti-cancer effect, can be assessedusing any of method known in the art, e.g., in vitro assays for exampleusing cell culture, or in vivo studies. Suitable assays are shown in theexamples.

In some embodiments, the anticancer live bacterial product induces aspecific immune cell population (e.g., CD8+ T-cells, Th17, Th1 cells).The abundance of a specific population of cells (e.g., CD8+ T-cells,Th17, Th1 cells) can be assessed by any method known in the art, forexample by detecting a cellular marker indicative of the cell type,assessing a direct or indirect activity of the cell type, and/or bymeasuring the production of one or more cytokines produced by thespecific cell type. In some embodiments, the anti-cancer live bacterialproduct induces CD8+ T-cells (or “CD8+ T cells”). As will be appreciatedby one of ordinary skill in the art, a combination of bacterial speciesand/or multiple strains from one or more species as described herein maybe selected and combined to produce an anti-cancer live bacterialproduct that induces CD8+ T-cells.

In one embodiment, the isolated bacteria, e.g. isolated bacterialstrains from the species listed herein, can be viable bacteria that arecapable of colonising the gastrointestinal gut of a subject whenadministered to said subject.

The inventors have shown that by combining bacteria from differentspecies, a therapeutic composition can be provided which finds use as aco-therapy with a checkpoint inhibitor. In a first aspect, the inventionrelates to a composition comprising isolated bacteria, e.g. a bacterialstrain, selected from one or more of the bacterial species B1, B2, B3,B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14 and/or B15 as shown inTable 1 or subsets thereof. The invention thus relates to a compositioncomprising one or more bacterial isolate, e.g. bacterial population,having a 16SrDNA selected from SEQ ID. Nos 1 to 19, e.g. 1 to 15. Theinvention thus relates to a composition comprising or consisting ofbacterial isolates of one or more of the species as shown in Table 1.

Table 1 below lists the 15 different bacterial species from which theisolated bacteria present in the composition are selected. Reference toexemplary 16S rDNA sequence characterising each species is also providedin Table 1. The terms 168S rDNA sequence or 16S rDNA as used hereinrefer to DNA nucleic acid sequences, i.e. a nucleic acid molecule, whichencodes 16S rRNA nucleic acid sequence i.e. a nucleic acid molecule.Nucleic acid sequences referenced below are fisted in Table 2. Also, asexplained further below, the bacteria of the composition and of otheraspects as described herein may have a 16S rDNA sequence with certainsequence identity to the SEQ ID Nos. as listed below.

TABLE 1 Bacterial species of the composition and biomarker signature 16SrDNA Possible alternative taxonomy: sequence - name and/or closelyrelated species sequence based on closely related bacteria No Taxonomyidentifier identified from public databases B1 Eisenbergiella sp. SEQ IDNo. 1; Eisenbergiella tayi SEQ ID No. 21 B2 Butyricicoccus sp. SEQ IDNo. 2; Butyricicoccus pullicaecorum, SEQ ID No. 17; bacteriumNLAE-zl-H41, bacterium SEQ ID No. 22 NLAE-zl-H55, bacterium NLAE-zl-H60B3 Clostridiales sp. SEQ ID No. 3 n/a B4 Alistipes obesi SEQ ID No. 4;n/a SEQ ID No. 16 B5 Alistipes indistinctus SEQ ID No. 5 n/a B6Gordonibacter SEQ ID No. 6; n/a urolithinfaciens SEQ ID No. 18; SEQ IDNo. 23 B7 Faecalitalea sp. SEQ ID No. 7; Longicatena caecimuris SEQ IDNo. 24 B8 Blautia sp. SEQ ID No. 8; Blautia products, Blautia coccoides,SEQ ID No. 25 Blautia marasmi, Blautia stercoris B9 Barnesiella SEQ IDNo. 9; n/a intestinihorninis SEQ ID No. 26 B10 Alistipes timonensis SEQID No. 10 n/a B11 Blautia sp. SEQ ID No. 11; n/a SEQ ID No. 19; SEQ IDNo. 27 B12 Lachnospira sp. SEQ ID No. 12; Lactobacillus rogosae SEQ IDNo. 20; SEQ ID No. 28 B13 Ruminococcus callidus SEQ ID No. 13 n/a B14Roseburia faecis SEQ ID No. 14; n/a SEQ ID No. 29 B15 FaecalibacteriumSEQ ID No. 15 n/a prausnitzii

The aspects and embodiments of the invention described herein aredefined by reference to the species name and/or SEQ ID NO. as shown inTable 1. In some cases, different exemplary sequences are provided inTable 1 for the same species, e.g. corresponding to different exemplarystrains which belong to the same species. Where multiple sequences areprovided for a species, these sequences share a high sequence identity,e.g. the different strains defined by SEQ ID No. 2 and SEQ ID No. 17have at least 99% sequence identity, SEQ ID No. 4 and SEQ ID No. 16 haveat least 99% sequence identity. SEQ ID No. 6 and SEQ ID No. 18 have atleast 99% sequence identity and SEQ ID No. 12 and SEQ ID No. 20 have atleast 99% sequence identity.

In the aspects and embodiments described herein, for each of B1 to B15,any of the sequences defined above (SEQ ID. Nos 1 to 29) can be used.Thus, where multiple sequences are provided for a single species, any ofthese sequences can be used.

It will be appreciated that the inventors provide compositions withcertain bacterial species that have immunostimulatory effects, e.g.anti-cancer effects. It will also be appreciated that for each species,different strains can be used, i.e. strains identified above or otherstrains that belong to the same species. It should be appreciated thatclosely related bacterial strains (e.g., as defined by 16S rDNAsequences) having similar or the same biological properties can also beincluded. In some embodiments, bacterial strains provided herein can bereplaced with bacterial strains with similar or the same biologicalproperties.

In some embodiments, the anticancer/live bacterial composition comprisesone or more bacterial strain of one or more of the 15 recited speciesshown in Table 1. In some embodiments, the anticancer/live bacterialcomposition comprises one or more bacterial strain of more than one ofthe 15 recited species; e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14or 15 species.

In one embodiment, the composition comprises or consists of 15 isolatedbacteria. e.g. bacteria from each of the 15 bacterial species listed inTable 1, for example with reference to the 18S rDNA sequences as shownin the Table or a sequence with certain percentage identity thereto asexplained below or with reference to the species name as shown above.

The invention also relates to compositions that comprise or consist ofbacteria selected from a subset of the bacterial species listed in Table1; e.g. compositions that comprise or consist of different bacteriaselected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 of thebacterial species listed in Table 1, with reference to the 16S rDNAsequences as shown in the Table 1 or a sequence with certain percentageidentity thereto as explained below or with reference to the speciesname as shown above. All combinations are envisaged.

Thus, in one embodiment, the composition comprises or consists of atleast one isolated bacterial population belonging to one or more of thespecies in Table 1. For example, the composition comprises or consistsof bacteria selected from 2, 3, 6, 9 or 12 bacterial species listed inTable 1. These may be selected from the consortia shown in Table 3, forexample consortia 2, 4, 5, 6 and 10. The bacteria may be defined byreference to their 16S rDNA as shown in the sequence identifiersTable 1. Thus, different bacteria selected from those listed in Table 1can be combined in a single composition.

For example, the composition comprises or consists of isolated bacteriaselected from at least 2, e.g. up to 3, up to 4, up to 5, up to 6, up to7, up to 8, up to 9, up to 10, up to 11, up to 12, up to 13, up to 14 orup to 15 species shown in Table 1, for example with reference to thesequences as shown in the Table. For example, the composition comprisesor consists of isolated bacteria from 9 bacterial species listed inTable 1. In one example, the composition comprises or consists ofisolated bacteria from 9 species as shown in Table 3, i.e. consortia 2,4, 5, 6 and 10. The bacteria may be defined by reference to their 16SrDNA as shown in the sequence identifiers in Table 1.

In one embodiment, the composition comprises or consists of isolatedbacteria selected from 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15species listed in Table 1, for example with reference to the sequenceIDs as shown in Table 1. In one embodiment, the composition comprises orconsists of isolated bacteria selected from the consortia in Table 3. Inone embodiment, the composition comprises or consists of isolatedbacteria having a 16S rDNA selected from the SEQ ID NOs. as shown inTable 1. The bacteria may be defined by reference to their 16S rDNA asshown in the sequence identifiers in Table 1. Sequences with certainpercentage sequence identify as shown herein are also within the scopeof the invention.

In one embodiment, the composition comprises isolated bacteria selectedfrom at least 2, at least 3, at least 4, at least 5, at least 6, atleast 7, at least 8, at least 9, at least 10, at least 11, at least 12,at least 13, at least 14 or at least 15 species listed in table 1, forexample with reference to the sequences as shown in table 1, for examplewith reference to the sequence IDs as shown in Table 1. In oneembodiment, the composition comprises isolated bacteria selected from atleast 9 species as shown in Table 1. Sequences with certain percentagesequence identify as shown herein are also within the scope of theinvention.

In one embodiment, the composition comprises or consists of isolatedbacteria selected from no more than 2, no more than 3, no more than 4,no more than 5, no more than 6, no more than 7, no more than 8, no morethan 9, no more than 10, no more than 11, no more than 12, no more than13, no more than 14 or no more than 15 species listed in Table 1, forexample with reference to the sequences as shown in table 1, for examplewith reference to the sequence IDs as shown in Table 1. Sequences withcertain percentage sequence identify as shown herein are also within thescope of the invention.

In one embodiment, the composition comprises or consists of isolatedbacteria selected from 2 to 4, 2 to 5, 2 to 6, 2 to 7, 2 to 8, 2 to 9, 2to 10, 2 to 11, 2 to 12, 2 to 13, 2 to 14 or 2 to 15 species shown intable 1, for example with reference to the sequences as shown in Table1, for example with reference to the sequence IDs as shown in Table 1.Sequences with certain percentage sequence identify as shown herein arealso within the scope of the invention.

In one embodiment, the composition comprises an isolated bacterialmixture comprising or consisting of 2 to 15 bacterial strains having atleast 90%, 95%, 97%, 98%, 98.7% or 99% sequence identity to 16s rDNAsequences selected from SEQ ID Nos 1 to 15, e.g. SEQ ID Nos. 16 to 29.Exemplary compositions are set out herein, e.g. In Table 3.

A skilled person would appreciate that that bacterial species selectedfrom Table 1 and for use in the composition and methods of the inventioncan have the sequence shown in Tables 1 and 2 or a sequence that hascertain percentage identity thereto and retains biological activity;i.e. activity against cancer/efficacy in enhancing the effect of atherapy using an immune checkpoint inhibitor.

In one embodiment, the composition may be as described above, but doesnot comprise bacteria of any other species, i.e. species not listed inTable 1 or the composition comprise only de minimis or biologicallyirrelevant amounts of bacteria from another species. By biologicallyirrelevant is meant bacteria that do not have an effect on the treatmentof cancer. Thus, in one embodiment, the composition consists of therecited bacteria.

In one embodiment, the composition does not comprise other bacterialspecies that fall within a genus listed in Table 1.

In one embodiment, the composition may comprise other bacterial speciesthat fall within a genus listed in Table 1, but does not comprisebacterial species of a genus not listed in Table 1. In one embodiment,the composition may comprise other bacterial species that fall within adifferent genus.

Methods of determining sequence identity are known in the art. It isknown that clades, operational taxonomic units (OTUs), species, andstrains are, in some embodiments, identified by their 16S rDNA sequence.The relatedness can be determined by the percent identity and this canbe determined using methods known in the art.

Bacterial species and strains used in a composition as described hereincan be identified based on the 16S nucleic acid sequence (full length orpart thereof, such as V regions). The 168S ribosomal DNA gene codes forthe DNA component of the 30S subunit of the bacterial ribosome. It iswidely present in all bacterial species. Different bacterial specieshave one to multiple copies of the 16S rRNA gene. 16S rRNA genesequencing is by far one of the most common methods targetinghousekeeping genes to study bacterial phylogeny and genus/speciesclassification. Thus, bacteria can be taxonomically classified based onthe sequence of the gene encoding the 16S nucleic acid sequence, e.g.ribosomal DNA (rDNA) in the bacterium. This gene sequence is alsoreferred to as the ribosomal DNA sequence (rDNA). The bacterial 16S rDNAis approximately 1500 nucleotides in length and is used inreconstructing the evolutionary relationships and sequence similarity ofone bacterial isolate to another using phylogenetic approaches. 16S rDNAsequences are used for phylogenetic reconstruction as they are ingeneral highly conserved, but contain specific hypervariable regionsthat harbor sufficient nucleotide diversity to differentiate genera andspecies of most microbes.

Using well known techniques to determine a full 16S rDNA sequence or thesequence of any hypervariable region of the 16S rDNA sequence, genomicDNA is extracted from a bacterial sample, the 16S rDNA (full region orspecific hypervariable regions) amplified using polymerase chainreaction (PCR), the PCR products cleaned, and nucleotide sequencesdelineated to determine the genetic composition of the 16S rDNA gene orsubdomain of the gene. If full 16S rDNA sequencing is performed, thesequencing method used may be, but is not limited to, Sanger sequencing.If one or more hypervariable regions are used, such as the V4 region,the sequencing may be, but is not limited to being, performed using theSanger method or using a next-generation sequencing method, such as anIllumina (sequencing by synthesis) method using barcoded primersallowing for multiplex reactions. The V1-V9 regions of the 16S rDNArefer to the first nine hypervariable regions of the 16S rDNA gene thatare often used for genetic typing of bacterial samples. In someembodiments, at least one of V1 to V9 is used to characterise thebacterial isolate.

In some embodiments, bacterial species identified as described hereinare identified by sequence identity to 16S rDNA sequences as known inthe art and described herein. In some embodiments, the selected speciesare identified by sequence identity to full length 16S rDNA sequences asshown in Table 2. In some embodiments, the selected species areidentified by sequence identity to a part of the 16S rDNA sequences asshown in Table 2, for example V3 and/or V4.

As used herein, the term “homology” or “identity” generally refers tothe percentage of nucleic acid residues in a sequence that are identicalwith the residues of the reference sequence with which it is compared,after aligning the sequences and in some embodiments after introducinggaps, if necessary, to achieve the maximum percentage homology, and notconsidering any conservative substitutions as part of the sequenceidentity. Thus, the percentage homology between two nucleic acidsequences is equivalent to the percentage identity between the twosequences. Methods and computer programs for the alignment are wellknown. The percentage identity between two sequences can be determinedusing well known mathematical algorithms.

In one embodiment, the degree of sequence identity between a querysequence and a reference sequence can be determined with the aid of acommercially available sequence comparison program. This typicallyinvolves aligning the two sequences using the default scoring matrix anddefault gap penalty, identifying the number of exact matches, anddividing the number of exact matches with the length of the referencesequence. Suitable computer programs useful for determining identityinclude, for example, BLAST (blast.ncbi.nlm.nih.gov).

In the various embodiments as set out herein when reference is made to aSEQ ID NO., sequences that have certain percentage sequence identity tothe full length sequence are also within the scope of the invention.

Thus, the full length or partial 16S rDNA of the bacterial specieslisted in Table 2 with reference to the sequence identifier in Table 1and which is used in the compositions and methods of the invention hasat least 90%, e.g. at least 91%, 92%. 93%, 94%, 95%, 96%, 97%, 98%,98.7%. 99%, 99.5% or 100% sequence identity to the correspondingreference 16S rDNA (i.e. SEQ IDs 1 to 29). In some embodiments, thethreshold sequence identity is at least 94.5%. In one embodiment, saidsequence identity is at least 95%. In one embodiment, said sequenceidentity is at least 96%. In one embodiment, said sequence identity isat least 97%. In one embodiment, said sequence identity is at least 98%.In one embodiment, said sequence identity is at least 98.7%. In oneembodiment, said sequence identity is at least 99%.

In one aspect, the composition therefore comprises two or more bacteria,that is bacterial species, comprising a 16S rDNA sequence selected fromSEQ ID NO. 1 to 15 or comprising a 16S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or98.7% identity to a nucleic acid sequence selected from SEQ ID NOs. 1 to15. Such sequences include SEQ ID. Nos 16 to 29, for example SEQ ID. Nos16 to 20.

In some embodiments, the threshold sequence identity is 94.5%, 94.6%,94.7%, 94.8%, 94.9%, 95.0%, 95.1%, 95.2%, 95.3%, 95.4%, 95.5%, 95.6%,95.7%, 95.8%, 95.9%, 96.0%, 96.1%, 96.2%, 96.3%, 96.4%, 96.5%, 96.6%,96.7%, 96.8%, 96.9%, 97.0%, 97.1%, 97.2%, 97.3%, 97.4%, 97.5%, 97.6%,97.7%, 97.8%, 97.9%, 98.0%, 98.1%, 98.2%, 98.3%, 98.4%, 98.5%, 98.6%,98.7%, 98.8%, 98.9% 99.0%, 99.1%, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%,99.7%, 99.8%, 99.9% or 100%.

In one embodiment, a bacterium present in the composition belongs to thesame species as a bacterium disclosed herein, has at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity to a nucleic acid sequence selected from SEQ ID NOs. 1 to 15and retains activity against cancer/efficacy in enhancing the effect ofa therapy using an immune checkpoint inhibitor. Such sequences includeSEQ ID. Nos 16 to 29, for example SEQ ID. Nos 16 to 20.

In one embodiment, the composition comprises or consists of one or moreof the following 15 bacteria having a 16sDNA of the following SEQ IDNos.:

SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%. 93%, 94%, 95%. 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 2 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%. 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 3 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 4 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 5 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 6 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 7 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 8 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 9 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 10 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 11 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 12 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 13 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 14 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto,

SEQ ID No. 15 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%. 93%, 94%. 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto.

Examples of the above are SEQ ID Nos. 16-29.

Thus, the composition comprises or consists of a population of bacteriathat belong to one or more of the 15 bacterial having a 16sDNA as shownabove.

In one embodiment, the composition does not include Faecalibacteriumprausnitzii (e.g. SEQ ID No. 15). In one embodiment, the compositiondoes not include Alistipes indistinctus (e.g. SEQ ID No. 5), Alistipesobesi (e.g. SEQ ID No. 4 or 16) and/or Alistipes timonensis (e.g. SEQ IDNo. 10).

In one embodiment, the composition comprises a consortium as shown inTable 3.

Thus, in one embodiment, the composition comprises or consists ofbacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or98.7% identity thereto, bacteria having SEQ ID No. 2 or a 16S rDNAsequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQID No. 3 or a 16S rDNA sequence having at least 90% e.g. at least 91%,92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto, bacteria having SEQ ID No. 4 or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%;e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No. 5, or a16S rDNA sequence having at least 90% e.g. at least 91%. 92%, 93%, 94%,95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteriahaving SEQ ID No. 6 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 7 or a 1S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%,98%, 99%; e.g. 97% or 98.7% identity thereto; bacteria having SEQ ID No.8 or a 1S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or a16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto and bacteriahaving SEQ ID No. 9 or a 1S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%. 94%, 95%, 96%. 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%. 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto (consortium 2 in Table 3).

In one embodiment, the composition comprises or consists of bacteriahaving SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 2 or a 16S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%. 94%, 95%, 96%. 97%,98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.3 or a 1S rDNA sequence having at least 90% e.g. at least 91%. 92%, 93%,94%, 95%, 96%, 97%. 98%, 99%; e.g. 97% or 98.7% identity thereto,bacteria having SEQ ID No. 6 or a 16S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%. 94%, 95%, 96%. 97%, 98%, 99%; e.g. 97% or98.7% identity thereto, bacteria having SEQ ID No. 7, or a 1S rDNAsequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQID No. 8 or a 16S rDNA sequence having at least 90% e.g. at least 91%.92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto, bacteria having SEQ ID No. 9 or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%;e.g. 97% or 98.7% identity thereto; bacteria having SEQ ID No. 11 or a16S rDNA sequence having at least 90% e.g. at least 91%, 92%. 93%, 94%.95%, 96%. 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or a 16SrDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%. 95%,96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto; bacteria havingSEQ ID No. 12 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto or a 16S rDNA sequence having at least 90% e.g. at least 91%,92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto, bacteria having SEQ ID No. 13 or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%;e.g. 97% or 98.7% identity thereto or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%. 98%, 99%;e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No. 14 or a16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,95%, 96%. 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or a 16SrDNA sequence having at least 90% e.g. at least 91%, 92%. 93%, 94%, 95%.96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto and bacteriahaving SEQ ID No. 15 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%. 98%, 99%; e.g. 97% or 98.7%identity thereto or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto (consortium 3 in Table 3).

In another embodiment, the composition comprises or consists of bacteriahaving SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto, SEQ ID No. 2 or a 16S rDNA sequence having at least90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97%or 98.7% identity thereto, bacteria having SEQ ID No. 3 or a 18S rDNAsequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQID No. 6 or a 16S rDNA sequence having at least 90% e.g. at least 91%,92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto, bacteria having SEQ ID No. 7 or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%;e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No. 8 or a16S rDNA sequence having at least 90% e.g. at least 91%, 92%. 93%, 94%,95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteriahaving SEQ ID No. 9 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%. 99%; e.g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 11 or a 16S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%. 96%, 97%,98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.14 or a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto(consortium 4 in Table 3).

In another embodiment, the composition comprises or consists of bacteriahaving SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 7 or a 16S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%. 97%,98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.8 or a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,bacteria having SEQ ID No. 9 or a 16S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or98.7% identity thereto, bacteria having SEQ ID No. 13 or a 16S rDNAsequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQID No. 16 or a 16S rDNA sequence having at least 90% e.g. at least 91%,92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto, bacteria having SEQ ID No. 17 or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%;e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No. 18 or a16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto and bacteriahaving SEQ ID No. 20 or a 16S rDNA sequence having at least 90% e.g. atleast 91%. 92%. 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto (consortium 5 in Table 3).

In another embodiment, the composition comprises or consists of bacteriahaving SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 2 or a 16S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%. 97%,98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.7 or a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,bacteria having SEQ ID No. 9 or a 18S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or98.7% identity thereto, bacteria having SEQ ID No. 13 or a 16S rDNAsequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQID No. 16 or a 16S rDNA sequence having at least 90% e.g. at least 91%,92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto, bacteria having SEQ ID No. 18 or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%;e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No. 19 or a16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto and bacteriahaving SEQ ID No. 20 or a 16S rDNA sequence having at least 90% e.g. atleast 91%. 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto (consortium 6 in Table 3).

In another embodiment, the composition comprises or consists of bacteriahaving SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 2 or a 16S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%. 97%,98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.7 or a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,bacteria having SEQ ID No. 9 or a 18S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or98.7% identity thereto, bacteria having SEQ ID No. 18 or a 16S rDNAsequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%; e.g. 97% or 98.7% identity thereto and bacteria havingSEQ ID No. 19 or a 16S rDNA sequence having at least 90% e.g. at least91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto (consortium 7 in Table 3).

In another embodiment, the composition comprises or consists of bacteriahaving SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%. 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 2 or a 168S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%. 97%,98%, 99%; e.g. 97% or 98.7% identity thereto and, bacteria having SEQ IDNo. 7 or a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto(consortium 8 in Table 3).

In another embodiment, the composition comprises or consists of bacteriahaving SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. atleast 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto and bacteria having SEQ ID No. 2 or a 16S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%,98%, 99%; e.g. 97% or 98.7% identity thereto (consortium 9 in Table 3).

Thus, in one embodiment, the composition comprises or consists ofbacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or98.7% identity thereto, bacteria having SEQ ID No. 2 or a 168S rDNAsequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQID No. 3 or a 16S rDNA sequence having at least 90% e.g. at least 91%,92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identitythereto, bacteria having SEQ ID No. 5 or a 16S rDNA sequence having atleast 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%. 99%;e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No. 7, or a16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteriahaving SEQ ID No. 10 or a 16S rDNA sequence having at least 90% e.g. atleast 91%. 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e g. 97% or 98.7%identity thereto, bacteria having SEQ ID No. 11 or a 16S rDNA sequencehaving at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%,98%, 99%; e.g. 97% or 98.7% identity thereto; bacteria having SEQ ID No.13 or a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,93%, 94%, 95%. 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto ora 16S rDNA sequence having at least 90% e.g. at least 91%. 92%, 93%,94%. 95%. 96%, 97%. 98%. 99%; e.g. 97% or 98.7% identity thereto andbacteria having SEQ ID No. 14 or a 16S rDNA sequence having at least 90%e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or98.7% identity thereto or a 168S rDNA sequence having at least 90% e.g.at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%identity thereto (consortium 10 in Table 3).

With reference to the percentage identities recited for the embodimentsof the compositions above, in one embodiments sequence identity is atleast 98.7% or 99%. It will be understood that where Table 1 providesmultiple sequences for a single species, any of these sequences can beused according to the above embodiments.

In one example, species used in the composition are identified based ontheir 16S rDNA sequence (e.g., full-length sequence, or partialsequence). In some cases, strains of bacterial species useful in aninvention, e.g., strains of the species disclosed herein, can beobtained from a public biological resource center such as the ATCC(atcc.org), the DSMZ (dsmz.de), or the Riken BioResource Center(en.brc.riken.jp). 16s rDNA sequences useful for identifying species orother aspects of the invention can be obtained from public databases,e.g., the Human Microbiome Project (HMP) web site or GenBank.

A skilled person would appreciate that the compositions may include oneor more than one strain of a particular bacterial species as listed inTable 1. For example, the composition of the invention comprises morethan one bacterial strain for a species. For example, in someembodiments, the composition of the invention comprises more than onestrain from within the same species (e.g. more than 1, 2, 3, 4, 5, 6, 7,8, 9, 10, 15, 20, 25, 30, 35, 40 or 45 strains). In another embodiment,the composition of the invention comprises one bacterial strain for eachspecies.

In one embodiment, the bacteria of the composition are capable ofcolonising the gastrointestinal tract of a subject. In one embodiment,the bacteria of the composition are capable of sustained engraftment inthe gastrointestinal tract of a subject.

In one embodiment, the composition has one or more of the followingcharacteristics:

-   -   The composition has an immunostimulatory effect;    -   The composition is effective in treating and/or preventing        cancer in a subject, tissue or cell. e.g. when used together        with a checkpoint inhibitor therapy;    -   The composition is effective in treating and/or preventing an        infectious disease in a subject, tissue or cell;    -   Administration of the composition to a subject, tissue or cell        induces an immune response in a subject and/or increases the        efficacy according to an anti-cancer therapy that includes an        immune checkpoint inhibitor,    -   Administration of the composition to a subject, tissue or cell        enhances CD8+ response;    -   Administration of the composition to a subject, tissue or cell        enhances immune checkpoint blockade;    -   Administering of the composition maintains or induces        responsiveness of a tumour an immune checkpoint;    -   Administration of the composition to a subject, tissue or cell        increases the number or activity of a cell type of the immune        system, e.g. T cells, B cells, dendritic cells, macrophages,        neutrophils, NK cells, plasmacytold dendritic cells and        combinations thereof;    -   Administration of the composition to a subject, tissue or cell        shifts a ratio of immune cells in the subject in favor of a cell        type capable of suppressing growth of a tumour e.g. T cells,        cytotoxic T lymphocytes, T helper cells, natural killer (NK)        cells, natural killer T (NKT) cells, plasmacytold dendritic        cells, anti-tumour macrophages, B cells, dendritic cells, and        combinations thereof and/or    -   Administration of the composition to a subject, tissue or cell        shifts a ratio of immune cells in the subject against a cell        type capable of protecting a tumour e.g. myeloid-derived        suppressor cells (MDSCs), regulatory T cells (Tregs), tumour        associated neutrophils (TANs), M2 macrophages, tumour associated        macrophages (TAMs), and a combination thereof;    -   Administration of the composition to a subject, tissue or cell        increases the abundance/level of bacteria in the subject which        discourages cancer/tumour growth, spread, and/or evasion of        treatment/immune response;    -   Administration of the composition to a subject, tissue or cell        increases the abundance of bacteria in the subject tissue or        cell which creates an environment or microenvironment (e.g.,        metabolome) that is conducive to the treatment of cancer and/or        inhibits cancer/tumour growth.

The subject may be a human or an animal in an animal model, for examplea mouse model. In vitro models can also be used for testing efficacy,e.g. tissue or cell-based models. Suitable models and assays are alsoshown in the examples.

As used herein, an “immune response” refers to the action of a cell ofthe immune system (e.g., T lymphocytes, B lymphocytes, natural killer(NK) cells, macrophages, eosinophils, mast cells, dendritic cells,neutrophils, etc.) and soluble macromolecules produced by any of thesecells or the liver (including antibodies, cytokines, and complement)that results in selective targeting, binding to, damage to, destructionof, and/or elimination from a subject of invading pathogens, cells ortissues infected with pathogens, or cancerous or other abnormal cells.This can be measured by assessing suitable markers or cell types.

As used herein, the term “immunotherapy” refers to the treatment orprevention of cancer by a method comprising inducing, enhancing,suppressing or otherwise modifying an immune response.

The bacterial isolates can be isolated and cultured as described inWO2013/171515 or WO2017/182796, both incorporated herein by reference.In one embodiment, bacterial strains are cultured and grown individuallyand then combined in the composition.

A bacterial isolate used in the composition is preferably anon-pathogenic strain. In other words, the bacterium preferably does notcause a disease in a healthy human individual when administered to saidindividual.

In one embodiment, each bacterium present in the composition issusceptible to treatment with one or more antibiotics. In other words,the bacterium is not resistant to treatment with at least oneantibiotic. This allows antibiotic treatment of an individual in theevent that one or more of the bacteria included in a therapeuticcomposition administered to the individual cause disease in theindividual, contrary to expectations. Thus, in one embodiment, thebacterium is susceptible to treatment with one or more antibioticsselected from the group consisting of: a beta-lactam, fusidic acid,elfamycin, aminoglycoside, fosfomycin, tunicamycin metronidazole and/orvancomycin. In vitro and in silico methods for screening bacteria forantibiotic resistance are known in the art.

In one embodiment, the isolated bacterium included in the compositionsmay not comprise one or more genes encoding one or more virulencefactors and/or preferably does not produce one or more virulencefactors. Virulence factors in this context are properties which enhancethe potential of a bacterium to cause disease in an individual.Virulence factors include the production of bacterial toxins, such asendotoxins and exotoxins by a bacterium, as well as the production ofhydrolytic enzymes that may contribute to the pathogenicity of thebacterium. Methods for screening bacteria for genes encoding virulencefactors are known in the art.

In some embodiments, one or more of the bacterial strains arehuman-derived bacteria, meaning the one or more bacterial strains wereobtained from or identified from a human or a sample therefrom (e.g., ahuman donor). In some embodiments of the compositions provided herein,all of the bacterial strains are human-derived bacteria. In someembodiments of the compositions provided herein, the bacterial strainsare derived from more than one human donor.

The bacterial strains used in the live bacterial products providedherein generally are isolated from the microbiome of healthyindividuals, e.g. from human faeces, but in some cases may not be fromhealthy individuals. In some embodiments, the live bacterial productsinclude strains originating from a single individual. In someembodiments, the live bacterial products include strains originatingfrom multiple individuals. In some embodiments, the bacterial strainsare obtained from multiple individuals, isolated and grown upindividually. The bacterial compositions that are grown up individuallymay subsequently be combined to provide the compositions of thedisclosure. It should be appreciated that the origin of the bacterialstrains of the live bacterial products provided herein is not limited tothe human microbiome from a healthy individual.

Isolation and characterisation can be achieved using standard methods inthe art. For example, the V4-V5 region of the 16S rRNA encoding gene canbe amplified and sequenced. Sequences can then be aligned and comparedto the 16S sequences provided herein for the bacterial isolates.Sequence protocols and alignment software are well known in the art.

In some cases, strains of bacterial species useful in an invention,e.g., strains of the species disclosed herein, can be obtained from apublic biological resource centre as described above.

In some embodiments in which the composition of the invention comprisesmore than one bacterial strain or species as listed herein, theindividual bacterial strains or species may be for separate,simultaneous or sequential administration. For example, the compositionmay comprise bacteria from all or a subset of the species listed inTable 1, or the bacterial strains or species are selected from thoselisted in Table 1, but may be stored separately and be administeredseparately, simultaneously or sequentially. In some embodiments, themore than one bacterial strain or species are stored separately, but aremixed together prior to use.

As explained herein, the bacterial compositions of the invention havetherapeutic effects when administered to a subject and can be used inthe treatment or prevention of cancer. Thus, the compositions asdescribed herein are therapeutic compositions. Thus, the invention alsoextends to pharmaceutical compositions comprising a composition ofbacteria as described herein. This may include further ingredients, forexample a vaccine.

In one embodiment, the composition may comprise a pharmaceuticallyacceptable excipient, carrier, buffer, stabilizer or other materialswell known to those skilled in the art. Such materials should benon-toxic and should not interfere with the efficacy of the isolatedbacteria present in the therapeutic composition. The precise nature ofthe pharmaceutically acceptable excipient or other material will dependon the route of administration, which may be oral or rectal. Manymethods for the preparation of therapeutic compositions are known tothose skilled in the art.

The bacterial compositions of the invention may comprise a prebiotic, apharmaceutically acceptable carrier, insoluble fibre, a buffer, anosmotic agent, an anti-foaming agent and/or a preservative. Particularexamples of excipients included in the composition are disclosed below.

Prebiotics may provide nutrients for the isolated bacteria present inthe bacterial composition to assist their early growth and colonisationafter administration to the individual. Any prebiotic known in the artmay be used. Non-limiting examples of prebiotics includeoligosaccharides, e.g., fructooligosaccharides such as oligofructose andinulin, mannan oligosaccharides and galactooligosaccharides, soluble,oligofructose-enriched inulin and soluble fibre. Insoluble fibre may beincluded in the therapeutic composition as a carrier, e.g., to provideprotection during transit or storage. A buffer may be included in thebacterial composition to promote the viability of the isolated bacteriapresent. An anti-fungal agent may be included in the bacterialcomposition as a preservative.

In one embodiment, the therapeutic bacterial compositions may compriseno other active ingredient other than the bacterial isolates asdescribed herein, including no other isolated bacterium, and optionallya prebiotic. Thus, the active ingredient of the therapeutic compositionmay consist of the group of bacterial isolates as described herein, andoptionally a prebiotic.

The bacterial compositions of the invention can be administered to asubject in a variety of ways as described in more detail elsewhereherein, including in the form of a capsule, tablet, gel or liquid.

The bacterial compositions of the invention may be for oral or rectaladministration to the subject. Where the composition is for oraladministration, the composition may be in the form of a capsule, or atablet. Where the therapeutic composition is for rectal administration,the therapeutic composition may be in the form of an enema, tablet orcapsule. The preparation of suitable capsules, tablets and enemas iswell-known in the art. The capsule or tablet may comprise an entericcoating to protect the capsule or tablet from stomach acid. For example,the capsule or tablet may be enteric-coated, pH dependent, slow-release,and/or gastro-resistant. Such capsules and tablets are used, forexample, to minimize dissolution of the capsule or tablet in the stomachbut allow dissolution in the small intestine. When intended for oraladministration, the composition can be in solid or liquid form, wheresemi-solid, semi-liquid, suspension and gel forms are included withinthe forms considered herein as either solid or liquid.

As a solid composition for oral administration, the composition can beformulated into a powder, granule, compressed tablet, pill, capsule,chewing gum, wafer or the like. Such a solid composition typicallycontains one or more inert diluents. In addition, one or more of thefollowing can be present: binders such as carboxymethylcellulose, ethylcellulose, microcrystalline cellulose, or gelatin, excipients such asstarch, lactose or dextrins, disintegrating agents such as alginic acid,sodium alginate, corn starch and the like; lubricants such as magnesiumstearate, glidants such as colloidal silicon dioxide, sweetening agentssuch as sucrose or saccharin, a flavoring agent such as peppermint,methyl salicylate or orange flavoring; and a coloring agent. When thecomposition is in the form of a capsule (e. g. a gelatin capsule), itcan contain, in addition to materials of the above type, a liquidcarrier such as polyethylene glycol, cyclodextrin or a fatty oil.

When intended for oral administration, a composition can comprise one ormore of a sweetening agent, preservatives, dye/colorant and flavorenhancer. In a composition for administration by injection, one or moreof a surfactant, preservative, wetting agent, dispersing agent,suspending agent, buffer, stabilizer and isotonic agent can also beincluded.

The bacterial composition may include a pharmaceutically acceptablecarrier or vehicle that can be particulate, so that the compositionsare, for example, in tablet or powder form. The term “carrier” refers toa diluent, adjuvant or excipient, with which the composition isadministered. Such pharmaceutical carriers can be liquids, such as waterand oils, including those of petroleum, animal, vegetable or syntheticorigin, such as peanut oil, soybean oil, mineral oil, sesame oil and thelike. The carriers can be saline, gum acacia, gelatin, starch paste,talc, keratin, colloidal silica, urea, and the like. In addition,auxiliary, stabilizing, thickening, lubricating and coloring agents canbe used. In one embodiment, the composition and pharmaceuticallyacceptable carriers are sterile. Saline solutions and aqueous dextroseand glycerol solutions can also be employed as liquid carriers,particularity for injectable solutions. Suitable pharmaceutical carriersalso include excipients such as starch, glucose, lactose, sucrose,gelatin, malt, rice, flour, chalk, silica gel, sodium stearate, glycerolmonostearate, talc, sodium chloride, dried skim milk, glycerol,propylene, glycol, water, ethanol and the like. The presentcompositions, if desired, can also contain minor amounts of wetting oremulsifying agents, or pH buffering agents.

The compositions can take the form of one or more dosage units. In anembodiment, the dose unit comprises at least 1×10³, 1×10⁴, 1×10⁵, 1×10⁶,1×10⁷, 1×10⁸, 1×10⁹, 1×10 ¹⁰, 1×10¹¹, 1×10¹², 1×10¹³ or greater than1×10¹³ colony forming units (cfu) of vegetative bacterial cells. In anembodiment, the dose unit comprises a pharmaceutically acceptableexcipient, an enteric coating or a combination thereof. The bacterialisolates or composition may be provided at a suitable dose.

Treatments or specific processes can be applied to improve the stabilityor viability of the bacterial isolates in the composition. The bacterialcomposition can be applied in a dry form or in a wet from. The bacterialcomposition may be lyophilized. The lyophilized therapeutic compositionmay comprise one or more stabilisers and/or cryoprotectants. Thelyophilized bacterial composition may be reconstituted using a suitablediluent prior to administration to the individual.

Then invention also relates to a pharmaceutical composition comprisingone or more bacteria of selected from the bacterial species of Table 1or comprising a composition as described herein and further comprisingan effective amount of an immune checkpoint inhibitor.

Immune checkpoints are regulatory pathways within the immune system thatare involved in maintaining immune homeostasis (e.g., self-tolerance,modulating the duration and extent of an immune response) to minimizecellular damage due to aberrant immune responses. Inhibitors of immunecheckpoints, herein referred to as “immune checkpoint inhibitors,”specifically inhibit immune checkpoints and may have a stimulatory orinhibitory effect on the immune response.

In one embodiment, the immune checkpoint inhibitor is an antibody orfragment thereof, an interfering nucleic acid molecule or anotherchemical entity.

A number of checkpoint inhibitors are known in the art and a number oftreatments have been approved by regulatory authorities, includingantibody treatments, whilst others, including treatments with monoclonalantibodies or antibody fragments, such as single domain antibodies, haveshown efficacy across a wide range of cancers.

In one embodiment, the immune checkpoint inhibitor inhibits PD-1activity, i.e. acts as PD-1 antagonist.

“PD-1 antagonist” or “PD-1 inhibitor” means any chemical compound orbiological molecule that blocks binding of PD-L1 expressed on a cancerand or immune cell to PD-1 expressed on an immune cell (T cell, B cellor NKT cell) and preferably also blocks binding of PD-L2 expressed on acancer and or immune cell to the immune-cell expressed PD-1.

In one embodiment, the immune checkpoint inhibitor is a PD-1 inhibitor,PD-L1 inhibitor or PD-L2 inhibitor, e.g. an anti PD-1 antibody or antiPD-L1 or anti PD-L2 antibody. In one embodiment, the immune checkpointinhibitor is an anti PD-1 antibody. In one embodiment, the immunecheckpoint inhibitor is an anti PD-1 or PD-L1 antibody optionallyselected from nivolumab (MDX-1106, MDX-1106-04, ONO-4538, orBMS-936558), pembrolizumab (Trade name KEYTRUDA® formerlyLambrolizumab®, also known as Merck 3745, MK-3475 or SCH-900475),cemiplimab, avelumab, durvalumab, atezolizumab, spartalizumab,camrelizumab, sintilimab, tislelizumab, pidilizumab or toripalimab.

In one embodiment, the immune checkpoint inhibitor is an anti-cytotoxicT-lymphocyte-associated protein 4 (CTLA-4 inhibitor), i.e. inhibits theactivity of CTLA-4. CTLA-4 (CD152) is a B7/CD28 family member thatinhibits T cell functions with NCBI Gene ID: 1493. CTLA-4 mAbs or CTLA-4ligands can prevent CTLA-4 from binding to its native ligands, therebyblocking the transduction of the T-cell negative regulating signal byCTLA-4 and enhancing the responsiveness of T-cells to various antigens.In this aspect, results from in vivo and in vitro studies aresubstantially in concert.

The CTLA4 inhibitor can be a CTLA4 antibody, optionally Ipilimumab orTremelimumab.

In one embodiment, the immune checkpoint inhibitor is an anti-TGIT,anti-LAG3 or anti-TIM3 agent, e.g. and antibody. The checkpoint targetslisted herein are not limiting and a skilled person would understandthat other checkpoint targets are also within the scope of the inventionand may be inhibited.

It should further be appreciated that multiple immune checkpointinhibitors may be used in the methods, compositions, and kits disclosedherein.

In some embodiments, the cancer immunotherapy agent comprises ananticancer vaccine (also referred to herein as a cancer vaccine). Cancervaccines generally act to increase an immune response to cancer cells.For example, cancer vaccines include cancer antigen(s) that act toinduce or stimulate an immune response against cells bearing the cancerantigen(s). The immune response induced or stimulated can include anantibody (humoral) immune response and/or a T-cell (cell-mediated)immune response.

Unless otherwise specified, the term PD-1 as used herein refers to humanPD-1. The terms “Programmed Death 1”, “Programmed Cell Death 1”,“Protein PD-1”, “PD-1”, PD1,” “PDCD1”, “hPD-1” and “hPD-1” are usedinterchangeably, and include variants, isoforms, species homologs ofhuman PD-1. The term PD-1 antibody or antibody fragment refers to amolecule capable of specifically binding to the human PD-1 antigen andantagonising PD-1 action. Human PD-1 amino acid sequences can be foundin NCBI Locus No.: NP_005009. Human PD-L1 and PD-L2 amino acid sequencescan be found in NCBI Locus No.: NP_054862 and NP_079515, respectively.

The term “antibody” as used herein broadly refers to any immunoglobulin(Ig) molecule, or antigen binding portion thereof, comprised of fourpolypeptide chains, two heavy (H) chains and two light (L) chains, orany functional fragment, mutant, variant, or derivation thereof, whichretains the essential epitope binding features of an Ig molecule. Suchmutant, variant, or derivative antibody formats are known in the art.The antibody may be mono or multispecific, e.g. bispecific. The antibodymay be administered in combination with another antibody therapy, e.g.another antibody that targets a checkpoint inhibitor or in combinationwith another anti-cancer therapy, e.g. chemotherapy and targetedtherapies, surgery and/or radiotherapy.

In a full-length antibody, each heavy chain is comprised of a heavychain variable region or domain (abbreviated herein as HCVR) and a heavychain constant region. The heavy chain constant region is comprised ofthree domains, CH1, CH2 and CH3. Each light chain is comprised of alight chain variable region or domain (abbreviated herein as LCVR) and alight chain constant region. The light chain constant region iscomprised of one domain, CL.

The heavy chain and light chain variable regions can be furthersubdivided into regions of hypervariability, termed complementaritydetermining regions (CDR), interspersed with regions that are moreconserved, termed framework regions (FR). Each heavy chain and lightchain variable region is composed of three CDRs and four FRs, arrangedfrom amino-terminus to carboxy-terminus in the following order: FR1,CDR1, FR2, CDR2, FR3, CDR3, FR4.

Immunoglobulin molecules can be of any type (e.g., IgG, IgE, IgM, IgD,IgA and IgY), class (e.g., IgG 1, IgG2, IgG 3, IgG4, IgA1 and IgA2) orsubclass.

The term antibody as used herein includes antibody fragments, such asF(ab′)2, Fab, Fv, scFv, a heavy chain only antibody, single domainantibodies (V_(H), V_(L), V_(HH)) or an antibody mimetic protein.Various antibody formats have been shown to show efficacy againstcheckpoint inhibitors, including single domain antibodies (e.g. Yu S etal. Nanobodies targeting immune checkpoint molecules for tumorimmunotherapy and immunoimaging. Int J Mol Med. 2021; 47(2):444-454).

scFv fragments (˜25 kDa) consist of the two variable domains, V_(H) andV_(L). Naturally, V_(H) and V_(L) domain are non-covalently associatedvia hydrophobic interaction and tend to dissociate. However, stablefragments can be engineered by linking the domains with a hydrophilicflexible linker to create a single chain Fv (scFv). The smallest antigenbinding fragment is the single variable fragment, namely the V_(H) orV_(L) domain. Binding to a light chain/heavy chain partner respectivelyis not required for target binding. Such fragments are used in singledomain antibodies. A single domain antibody (˜12 to 15 kDa) thereforehas either the V_(H) or V_(L) domain.

The antibody may be human, humanised or chimeric. A chimeric antibody isa recombinant protein that contains the variable domains including thecomplementarity determining regions (CDRs) of an antibody derived fromone species, preferably a rodent antibody, while the constant domains ofthe antibody molecule are derived from those of a human antibody.

A humanized antibody is a recombinant protein in which the CDRs from anantibody from one species; e.g., a rodent antibody, are transferred fromthe heavy and light variable chains of the rodent antibody into humanheavy and light variable domains (e.g., framework region sequences). Theconstant domains of the antibody molecule are derived from those of ahuman antibody. In certain embodiments, a limited number of frameworkregion amino acid residues from the parent (rodent) antibody may besubstituted into the human antibody framework region sequences.

Checkpoint inhibitors are not limited to antibodies. In one embodiment,the immune checkpoint inhibitor is an interfering nucleic acid molecule,optionally wherein the interfering nucleic acid molecule is an siRNAmolecule, an shRNA molecule or an antisense RNA molecule.

In one embodiment, the immune checkpoint inhibitor is a small moleculeor PROteolysis TArgeting Chimera (PROTAC), alternative scaffold protein,biologics or other immune checkpoint inhibitor. In one embodiment, theimmune checkpoint inhibitor is an interfering nucleic acid molecule. Inone embodiment, the interfering nucleic acid molecule is an siRNAmolecule, an shRNA molecule or an antisense RNA molecule. In oneembodiment, the immune checkpoint inhibitor is a small molecule or aPROteolysis TArgeting Chimera (PROTAC) or other immune checkpointinhibitor. Examples that small molecules can be used as checkpointinhibitors is provided by research on sulfamonomethoxine andsulfamethizole. Exemplary small molecule compounds that inhibit PD-L1are disclosed in U.S. Pat. No. 9,850,225 incorporated herein byreference. A small molecule currently in human clinical trials is amolecule called Ca-170, which inhibits both the PD-L1 pathway and theV-domain Ig suppressor of the T-cell activation (VISTA) pathway.

In one embodiment, the immune checkpoint inhibitor is a peptideinhibitor. An example is the peptide antagonist. (D)PPA-1, which blocksthe PD-1/PD-L1 interaction and decreases tumor growth in vivo (Chang H.N et al. Blocking of the PD-1/PD-L1 interaction by a D-PeptideAntagonist for Cancer Immunotherapy. Angew. Chem. Int. Ed. 2015;54:11760-11764). Another peptide inhibitor is PL120131, shown to act asa competitive inhibitor of PD-L1 (Magiera-Mularz K. et al BioactiveMacrocyclic Inhibitors of the PD-1/PD-L1 Immune Checkpoint. Angew. Chem.Int. Ed. 2017; 56:13732-13735) and TPP-1 (Li C., Zhang N et al, PeptideBlocking of PD-1/PD-L1 Interaction for Cancer Immunotherapy. CancerImmunol. Res. 2018; 6:178-188).

In another aspect, there is provided a bacterial composition describedherein for use in the treatment of disease. e.g. cancer. In anotheraspect, there is provided the use of a bacterial composition describedherein in the manufacture of a medicament for the treatment orprevention of a disease, e.g. cancer.

In another aspect, there is provided a method for treating or preventinga disease comprising administering a bacterial composition describedherein to a subject. In another aspect, there is provided a method fortreating or preventing a disease in a subject comprising modulating thelevel of, e.g. Increasing the level/relative abundance of one or morebacterium selected from B1, B2, B3, B4, B5, B8, B7, B8, B9, B10, B11,B12, B13, B14 and/or B15 as shown in Table 1 or a subset thereof in asubject. In one embodiment, the subset comprises or consists of bacteriaselected from 1, 2, 3, 4, 5, 8, 7, 8, 9, 10, 11, 12, 13, 14 or 15bacterial species shown in Table 1. Modulating the level according toone or more bacterium in the subject enhances an immune response by thesubject and/or inhibits immune evasion by the cancer and/or increasesefficacy according to an anti-cancer treatment with an immune checkpointinhibitor. In one embodiment, the method comprises administering acomposition as described herein.

As explained below, the level/abundance can be compared to a referencevalue from a reference subject or population of subjects.

In one embodiment, the disease is cancer. In one embodiment, the canceris melanoma. “Melanoma” is taken to mean a tumour arising from themelanocytic system of the skin and other organs. Non-limiting examplesof melanomas are Harding-Passey melanoma, juvenile melanoma, lentigomaligna melanoma, malignant melanoma, acral-lentiginous melanoma,amelanotic melanoma, benign juvenile melanoma, Cloudman's melanoma, S91melanoma, nodular melanoma, subungual melanoma, Cutaneous melanoma,uveal/intraocular melanoma and superficial spreading melanoma.

The compositions of the present invention are particularly useful forthe treatment of cancers that are treatable by checkpoint inhibitors.

In one embodiment, the cancer is associated with cells (e.g., exhaustedT cells, B cells, monocytes, etc.) that express abnormally high levelsof PD-1. Other cancers include those characterized by elevatedexpression of PD-1 and/or its ligands PD-L1 and/or PD-L2.

In one embodiment, the cancer is selected from a cancer that has highlevels of cancer-associated genetic mutations and/or high levels ofexpression of tumour antigens. In another embodiment, the cancer isselected from a cancer known to be immunogenic or that is able to becomeimmunogenic upon treatment with other cancer therapies. In a furtherembodiment the cancer can be selected from a cancer generally treated bynon-immunological therapies, such as chemotherapy, in which thepatient's immune system is likely to have a role.

The cancer can be selected from a solid or non-solid tumour. Forexample, in addition to melanoma, the cancer may be selected fromanother skin cancer or from bone cancer, pancreatic cancer, cancer ofthe head or neck, cutaneous or intraocular malignant melanoma, uterinecancer, ovarian cancer, rectal cancer, cancer of the anal region,stomach cancer, testicular cancer, breast cancer, brain cancer,carcinoma of the fallopian tubes, carcinoma of the endometrium,carcinoma of the cervix, carcinoma of the vagina, carcinoma of thevulva, cancer of the esophagus, cancer of the small intestine, cancer ofthe endocrine system, cancer of the thyroid gland, cancer of theparathyroid gland, cancer of the adrenal gland, kidney cancer, sarcomaof soft tissue, cancer of the urethra, cancer of the bladder, renalcancer, lung cancer, non-small cell lung cancer, thymoma, urothelialcarcinoma leukemia, prostate cancer, mesothelhoma, adrenocorticalcarcinoma, lymphomas, such as such as Hodgkin's disease, non-Hodgkin's,gastric cancer, and multiple myelomas.

In one embodiment, the tumour is a solid tumour. Examples of solidtumours which may be accordingly treated include breast carcinoma, lungcarcinoma, colorectal carcinoma, pancreatic carcinoma, glioma andlymphoma. Some examples of such tumours include epidermoid tumours,squamous tumours, such as head and neck tumours, colorectal tumours,prostate tumours, breast tumours, lung tumours, including small cell andnon-small cell lung tumours, pancreatic tumours, thyroid tumours,ovarian tumours, and liver tumours. Other examples include Kaposi'ssarcoma, CNS, neoplasms, neuroblastomas, capillary hemangioblastomas,meningiomas and cerebral metastases, melanoma, gastrointestinal andrenal carcinomas and sarcomas, rhabdomyosarcoma, glioblastoma,preferably glioblastoma multiforme, and lelomyosarcoma. Examples ofvascularized skin cancers for which the antagonists of this inventionare effective include squamous cell carcinoma, basal cell carcinoma andskin cancers that can be treated by suppressing the growth of malignantkeratinocytes, such as human malignant keratinocytes. In one embodiment,the cancer is NSCL.

In one embodiment, the tumour is a non-solid tumour. Examples ofnon-solid tumours include leukemia, multiple myeloma and lymphoma.

In one aspect, the cancer is identified as a PD-1 and/or PD-L1 positivecancer or a cancer positive for another checkpoint protein. In oneaspect, the cancer is locally advanced, unresectable, metastatic, orrecurrent cancer.

Preferred cancers whose growth may be inhibited using the agents of theinvention include cancers typically responsive to immunotherapy.Non-limiting examples of preferred cancers for treatment includemelanoma (e.g., metastatic malignant melanoma), renal cancer (e.g. clearcell carcinoma), prostate cancer (e.g. hormone refractory prostateadenocarcinoma), breast cancer, colon cancer and lung cancer (e.g.non-small cell lung cancer).

As used herein, “treat”, “treating” or “treatment” means inhibiting orrelieving a disease or disorder. For example, treatment can include apostponement of development of the symptoms associated with a disease ordisorder, and/or a reduction in the severity of such symptoms that will,or are expected, to develop with said disease. The terms includeameliorating existing symptoms, preventing additional symptoms, andameliorating or preventing the underlying causes of such symptoms. Thus,the terms denote that a beneficial result is being conferred on at leastsome of the mammals, e.g., human patients, being treated. Many medicaltreatments are effective for some, but not all, patients that undergothe treatment.

The term “subject” or “patient” refers to an animal, e.g. a human, whichis the object of treatment, observation, or diagnosis. By way of exampleonly, a subject includes, but is not limited to, a mammal, including,but not limited to, a human or a non-human mammal, such as a non-humanprimate, murine, bovine, equine, canine, ovine, or feline. In oneembodiment, the subject is a cancer patient that has received prioranti-cancer treatment or is receiving anti-cancer treatment. In oneembodiment, the anti-cancer treatment is treatment with an immunecheckpoint inhibitor. Exemplary immune checkpoint inhibitors aredescribed herein.

The term “anti-cancer therapy” refers to any therapeutic regimen thataims to reduce or eliminate cancer, slow the progression of cancer,prevent or reduce the risk of cancer metastasis, and/or reduce orprevent any one or more symptoms associated with cancer. The anti-cancertherapies described herein involve administering anti-cancer therapiesto a subject, e.g., a subject having cancer or at risk of having cancer.

Administration according to the method and uses above includes oraladministration or rectal administration.

In one embodiment, the subject has received prior anti-cancer therapywith an immune checkpoint inhibitor. In one embodiment, an anti-cancertherapy comprising an immune checkpoint inhibitor is administered to thesubject. This can be administered at the same time as the composition ofthe invention, either as part of the same medicament or as a secondmedicament. It can also be administered prior or after theadministration of the composition of the invention. Other treatmentschedules are also within the scope of the invention.

In one embodiment, the immune checkpoint inhibitor is administeredbefore, after or at the same time as the bacterial composition. In oneembodiment, checkpoint therapy is initiated, and then supplemented withtreatment using the bacterial composition described herein if noresponse is seen after 3-8 months.

In one embodiment, the immune checkpoint inhibitor is administered afterthe bacterial composition. In one embodiment the immune checkpointinhibitor is administered by injection/infusion. In one embodiment theinjection is an intravenous, intramuscular, intratumoural orsubcutaneous injection.

Checkpoint inhibitors that can be used in accordance with the treatmentaspects are defined above. For example, the immune checkpoint inhibitorinhibits PD-1, CTLA-4 or PD-L1 activity. In one embodiment the immunecheckpoint inhibitor is an anti PD-1, CTLA-4 or PD-L1 antibody. In oneembodiment, the anti PD-1, CTLA-4 or PD-L1 antibody is selected fromnivolumab, pembrolizumab, cemiplimab, avelumab, durvalumab,atezolizumab, Spartalizumab, Camrelizumab, Sintilimab, Tislelizumab,Pklizumab or Toripaflmab, Ipilimumab or Tremelimumab.

The amount of the antibody that is effective/active in the treatment ofa particular disorder or condition will depend on the nature of thedisorder or condition and can be determined by standard clinicaltechniques. In addition, in vitro or in vivo assays can optionally beemployed to help identify optimal dosage ranges. The precise dose to beemployed in the compositions will also depend on the route ofadministration, and the seriousness of the disease or disorder, andshould be decided according to the judgment of the practitioner and eachpatient's circumstances. Factors like age, body weight, sex, diet, timeof administration, rate of excretion, condition of the host, drugcombinations, reaction sensitivities and severity of the disease shallbe taken into account.

Typically, the amount is at least about 0.01% of an anti-PD-1, CTL-4 orPD-L1 antibody by weight of the composition. When intended for oraladministration, this amount can be varied to range from about 0.1% toabout 80% by weight of the composition. Oral compositions can comprisefrom about 4% to about 50% of the antibody by weight of the composition.

Antibody compositions can be prepared so that a parenteral dosage unitcontains from about 0.01% to about 2% by weight of the antibody.

For administration by injection, the composition can comprise from abouttypically about 0.1 mg/kg to about 250 mg/kg of the animal's bodyweight, preferably, between about 0.1 mg/kg and about 20 mg/kg of theanimal's body weight, and more preferably about 1 mg/kg to about 10mg/kg of the animal's body weight. In one embodiment, the composition isadministered at a dose of about 1 to 30 mg/kg, e.g., about 5 to 25mg/kg, about 10 to 20 mg/kg, about 1 to 5 mg/kg, or about 3 mg/kg. Thedosing schedule can vary from e.g., once a week to once every 2, 3, or 4weeks.

In one embodiment, the immune checkpoint inhibitor is an interferingnucleic acid molecule. In one embodiment, the interfering nucleic acidmolecule is an siRNA molecule, an shRNA molecule or an antisense RNAmolecule. In one embodiment, the immune checkpoint inhibitor is a smallmolecule or a PROteolysis TArgeting Chimera (PROTAC) or other immunecheckpoint inhibitor, for example as described above.

In one embodiment, the method and uses further comprise administrationof an anti-cancer therapy, e.g. a second anti-cancer therapeutic inaddition to an immune checkpoint inhibitor. The anti-cancer therapy mayinclude a therapeutic agent or radiation therapy and includes genetherapy, viral therapy, RNA therapy bone marrow transplantation,nanotherapy, targeted anti-cancer therapies or oncolytic drugs or acombination thereof. Examples of other therapeutic agents include othercheckpoint inhibitors, antineoplastic agents, immunogenic agents,attenuated cancerous cells, tumour antigens, antigen presenting cellssuch as dendritic cells pulsed with tumour-derived antigen or nucleicacids, immune stimulating cytokines (e.g., IL-2, IFNa2, GM-CSF),targeted small molecules and biological molecules (such as components ofsignal transduction pathways, e.g. modulators of tyrosine kinases andinhibitors of receptor tyrosine kinases, and agents that bind totumour-specific antigens, including EGFR antagonists), ananti-inflammatory agent, a cytotoxic agent, a radiotoxic agent, or animmunosuppressive agent and cells transfected with a gene encoding animmune stimulating cytokine (e.g., GM-CSF), chemotherapy. In oneembodiment, the composition is used in combination with surgery. In oneembodiment, the composition is used in combination with a stem-celltransplant therapy comprising a peripheral blood transplant, a bonemarrow transplant, a cord blood transplant, or a skin-derived stem celltransplant.

In one embodiment, the composition is used in combination with adoptivecell transfer (ACT). In general, adoptive cell transfer therapy involvesharvesting cells from a subject, specifically producing or expanding aspecific cell population, optionally activating the cells, andadministering the expanded cells to the subject. In some embodiments,the desired cells are immune cells capable of killing or eliminatingcancer cells.

In some embodiments, the adoptive cell transfer therapy uses engineeredT-cell receptors or chimeric antigen receptors, which may be referred toas CAR-T therapy. CAR-T cells include T-cells taken from a subject thatare genetically engineered to express chimeric antigen receptors (CARs)on the cell surface. The CAR-T cell receptors are designed to recognizea specific antigen on cancer cells (e.g., a cancer antigen). After theCAR-T cells are infused into the subject, the CAR-T cells recognize andkill cancer cells that express the specific antigen on their surfaces.In some embodiments, the CAR-T cells are autologous cells, meaning the Tcells were harvested and re-administered to the same subject. In someembodiments, the CAR-T cells are CD8+ T cells. In some embodiments, theCAR-T cells are allogeneic cells, meaning the T cells were harvestedfrom one subject (e.g., the donor) and administered to a differentsubject (e.g., the recipient).

Examples of cancer antigens that may be targeted by CAR-T cells areknown in the art, and selection of a cancer antigen for targeting willdepend on factors such as the cancer that is being targeted.

In some embodiments, the anticancer therapy involves administering oneor more costimulatory agents. In some embodiments, the costimulatoryagent is a molecule that targets one or more costimulatory molecules,thereby modulating the immune response. In some embodiments, thecostimulatory agent enhances an anticancer immune response, for example,by preventing the downregulation of an immune response. A costimulatoryagent may be administered alone in a cancer therapy or in combinationwith one or more cancer therapies to enhance the therapeutic effect ofthe cancer therapy. In some embodiments, the costimulatory agent is anantibody that targets CD-28, OX-40, 4-1BB, or CD40.

In one embodiment of the present invention, the composition isadministered concurrently with a chemotherapeutic agent and/or withradiation therapy. In another specific embodiment, the chemotherapeuticagent and/or radiation therapy is administered prior or subsequent toadministration of the composition of the present invention, preferablyat least an hour, five hours, 12 hours, a day, a week, a month, morepreferably several months (e. g. up to three months), prior orsubsequent to administration of composition of the present invention.

As used herein, a chemotherapy agent refers to a molecule (e.g., drug)that specifically or preferentially kills cancer cells or prevents theproliferation of cancer cells. Chemotherapy agents can generally becategorized based on the molecular target of the chemotherapy agent, themechanism of action, and/or the structure of the agent. In someembodiments, the chemotherapy agent is an alkylating agent, a plantalkaloid, an antitumor antibiotic, an antimetabolite, a topoisomeraseinhibitor, or other antineoplastic agent.

In one embodiment, the chemotherapeutic agent is selected from the groupconsisting of alkylating agents, alkyl sulfonates, aziridines, anethylenimine, a methylamelamine, an acetogenin, a camptothecinbryostatin, cally statin, CC-1065, a cryptophycin, dolastatin,duocarmycin, eleutherobin, pancratistatin, a sarcodictyin, spongistatin,a nitrogen mustard, a nitrosurea, an antibiotic, a dynemicin; abisphosphonate, an esperamicin, neocarzinostatin chromophore and relatedchromoprotein enediyne antibiotic chromophores, an aclacinomysin,actinomycin, authramycin, azaserine, bleomycins, cactinomycin,carabicin, caminomycin, carzinophilin, chromomycinis, dactinomycin,daunorubicin, detorubicin, 6-diazo-5-oxo-L-norleucine, ADRIAMYCINdoxorubicin, epirubicin, esorubicin, idarubicin, marcellomycin, amitomycin, mycophenolic acid, nogalamycin, an olivomycin, peplomycin,potfiromycin, puromycin, quelamycin, rodorubicin, streptonigrin,streptozocin, tubercidin, ubenimex, zinostatin, zorubicin ananti-metabolite, a folic acid analogue, a purine analog, a pyrimidineanalog, an androgen, an anti-adrenal, a folic acid replenishesaceglatone, aldophosphamide glycoside, aminolevulinic acid, eniluracil,amsacrine, bestrabucil, bisantrene, edatrexate, demecolcine, diaziquone,elformithine, elliptinium acetate, an epothilone, etoglucid, galliumnitrate, hydroxyurea, lentinan, lonidainine, a maytansinoid,mitoguazone, mitoxantrone, mopidanmol, nitraerine, pentostatin,phenamet, pirarubicin, losoxantrone, podophyllinic acid,2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane,rhizoxin, sizofuran, spirogermanium, tenuazonic acid, triaziquone,2,2′,2″-trichlorotriethylamine, a trichothecene, urethan, vindesine,dacarbazine, mannomustine, mitobronitol, mitolactol, pipobroman,gacytosine, arabinoside (“Ara-C”), cyclophosphamide, thiotepa, a taxoid,ABRAXANE Cremophor-free, an albumin-engineered nanoparticle formulationof paclitaxel and TAXOTERE doxetaxel, chlorambucil, GEMZAR gemcitabine,6-thioguanine, mercaptopurine, methotrexate, a platinum analog,vinblastine, platinum, etoposide (VP-16), ifosfamide, mitoxantrone,vincristine, NAVELBINE, vinorelbine, novantrone, teniposide, edatrexate,daunomycin, aminopterin, xeloda, ibandronate, irinotecan (Camptosar,CPT-11), topoisomerase inhibitor RFS 2000; difluoromethylornithine(DMFO), a retinoid, capecitabine, combretastatin, leucovorin (LV),oxaliplatin, Binimetinib (Mektovi), Encorafenib (Braftovi), lapatinib(TYKERB), an inhibitor of PKC-a, an inhibitor of Raf, an inhibitor ofH-Ras, an inhibitor of EGFR, an inhibitor of VEGF-A, pharmaceuticallyacceptable salt, acid or derivative thereof, and combinations thereof.

In some embodiments, the composition of the invention may beadministered with two or more (e.g., 2, 3, 4, 5, or more) therapeuticagents.

In one embodiment, administration is together with an agent involved inT-cell activation, a tumour microenvironment modifier (TME) or atumour-specific target.

In one embodiment, the method and uses further comprise administering anantibiotic to the subject.

In yet another aspect, the invention provides a method of modulating animmune response in a subject comprising administering to the subject acomposition of the invention.

In some embodiments, the individual has cancer that is resistant (hasbeen demonstrated to be resistant) to one or more anti-cancer therapies.In some embodiments, resistance to anti-cancer therapy includesrecurrence of cancer or refractory cancer. Recurrence may refer to thereappearance of cancer, in the original site or a new site, aftertreatment. In some embodiments, resistance to anti-cancer therapyincludes progression of the cancer during treatment with the anti-cancertherapy. In some embodiments, the cancer is at early stage or at latestage.

The composition of the invention has immunostimulatory properties.Therefore, use of the composition is not limited to the treatment ofcancer. Thus, due to the immunostimulatory properties, the compositionfinds use in the treatment of any disease which requiresimmunostimulation, e.g. non-cancer immunotherapies. Immunotherapy iscollectively defined as a therapeutic approach that targets ormanipulates the immune system. Ultimately, immunotherapy aims to harnessthe host's adaptive and innate immune response to effectuate long-livedelimination of diseased cells and can be categorized broadly intopassive (including adoptive and antibody-based) and active (includingvaccine therapy and allergen-specific) approaches. Passive-mediatedimmunotherapy involves the administration of ex vivo-generated immuneelements (antibodies, immune cells) to patients and does not stimulatethe host immune response, while active immunotherapy induces thepatient's immune response and results in the development of specificimmune effectors (antibodies and T cells). Immunotherapy offers apossible modality to improve the ability to prevent or treat infectiousdiseases (Naran et al, Front Microbiol. 2018; 9: 3158). Thus, in someembodiments, the disease is an infectious disease.

The recent success of PD-1 and PD-L1 blockade in cancer therapyillustrates the important role of the PD-1/PD-L1 pathway in theregulation of antitumor immune responses. However, signaling regulatedby the PD-1/PD-L pathway is also associated with substantialinflammatory effects that can resemble those in autoimmune responses,chronic infection, and sepsis, consistent with the role of this pathwayin balancing protective immunity and immunopathology, as well as inhomeostasis and tolerance (Qin et al, Front Immunol. 2019; 10: 2298; Raoet al, Int. J. Infect. Dis. 2017; 56: 223). Thus, in another aspect, theinvention provides a composition as described herein; e.g. comprisingone or more of B1 to B15 as in table 1, e.g. a composition with one ormore bacterial isolate having a 16SrDNA having a sequence selected fromSEQ ID Nos. 1 to 15 or a sequence with at least 97%, 98%, 98.7% or 99%sequence identity thereto, e.g. SEQ ID Nos. 16-29, for use in thetreatment of an infectious disease. Also provided is a method for thetreatment of an infectious disease comprising administering acomposition of the invention to a subject. Also covered is a compositionas described herein for use in the manufacture of a medicament for thetreatment of an infectious disease.

An infectious disease may be a viral, fungal and bacterial infection.The infectious disease may be a chronic infectious disease. Non-limitingexamples include human immunodeficiency virus (HIV), hepatitis B (HBV),hepatitis C (HCV), JC (John Cunningham) virus/progressive multifocalleukoencephalopathy and tuberculosis.

Treatment of infections with the composition of the invention can be asco-therapy with an immunotherapy, for example an immune checkpointinhibitor, other anti-virals or anti-infectives.

In another aspect, the invention provides a composition as describedherein, e.g. comprising one or more of B1 to B15 as in table 1, e.g. acomposition with one or more bacterial isolate having a 16S rDNA havinga sequence selected from SEQ ID Nos. 1 to 15 or a sequence with at least97%, 98%, 98.7% or 99% sequence identity thereto, for use as a vaccineadjuvant. Also provided is a method for increasing vaccine efficacycomprising administering a composition as described herein, e.g.comprising one or more of B1 to B15 as in Table 1, e.g. a compositionwith one or more bacterial isolate having a 16S rDNA having a sequenceselected from SEQ ID Nos. 1 to 15 or a sequence with at least 97%, 98%,98.7%, 99% or 100% sequence identity thereto, e.g. SEQ ID Nos. 16-29, toa subject. Said subject may receive a vaccine before, after orconcurrently with administration of the bacterial composition.

Administration may be in a “therapeutically effective amount”, thisbeing sufficient to show benefit to the individual. Such benefit may beat least amelioration of at least one symptom. Thus “treatment” of aspecified disease refers to amelioration of at least one symptom. Theactual amount administered, and rate and time-course of administration,will depend on the nature and severity of what is being treated, theparticular patient being treated, the clinical condition of theindividual patient, the site of delivery of the composition, the type oftherapeutic composition, the method of administration, the scheduling ofadministration and other factors known to medical practitioners.Prescription of treatment, e.g. decisions on dosage etc., is within theresponsibility of general practitioners and other medical doctors andmay depend on the severity of the symptoms and/or progression of adisease being treated. A therapeutically effective amount or suitabledose of a therapeutic composition of the invention can be determined bycomparing its in vitro activity and in vivo activity in an animal model.Methods for extrapolation of effective dosages in mice and other testanimals to humans are known. The precise dose will depend upon a numberof factors, including whether the therapeutic composition is forprevention or for treatment.

In one embodiment of the methods which require administration of thecomposition, the method includes the further step of detecting thepresence of one or more of the bacterial strain that has beenadministered in the subject subsequent to administration. Methods fordetection include for example detecting a 16S nucleic acid sequence asdefined herein of at least one administered bacterial isolate in saidsubject.

The composition of the present invention may be prepared by a methodcomprising culturing the two or more isolated bacteria present in thecomposition in a suitable medium or media. Media and conditions suitablefor culturing the bacteria to be included in the therapeutic compositionof the present invention are described in detail elsewhere herein. Forexample, a method of preparing a therapeutic composition according tothe present invention may comprise the steps of:

(i) culturing a first isolated bacterium;

(ii) culturing a second and optionally a further isolated bacterium; and

(iii) mixing the bacteria obtained in (i) and (ii) to prepare thetherapeutic composition.

The isolated bacteria to be included in the composition may be culturedin separate steps. In other words, a separate culture of each bacteriumto be included in the therapeutic composition is preferably prepared.This allows the growth of each bacterium to be evaluated and the amountof each bacterium to be included in the pharmaceutical composition to becontrolled as desired. The bacteria cultured in steps (i) and (ii)preferably have distinct 16S nucleic acid sequences, that is 16S nucleicacid sequences that share less than 99%, 98%, 97%, 96% or 95% sequenceidentity. The above method may include steps of culturing each isolatedbacterium which is to be included in the composition.

The method may optionally comprise one or more further steps in whichthe bacteria are mixed with one or more additional ingredients, such asa pharmaceutically acceptable excipient, prebiotic, carrier, insolublefibre, buffer, osmotic agent, antifoaming agent, and/or preservative. Inaddition, or alternatively, the method may comprise suspending thebacteria obtained in (i) and optionally (i) in a chemostat medium, orsaline, e.g. 0.9% saline. The bacteria obtained in (i) and optionally(ii) may be provided under a reduced atmosphere, such as N2, CO2, H2, ora mixture thereof, e.g. N2:CO2:H2. The gases may be present inappropriate ratios for the preservation of the bacteria present in thetherapeutic composition. For example, the reduced atmosphere maycomprise 80% N2, 10% CO2 and 10% H2. In addition, or alternatively, themethod may comprise a step of lyophilising the bacteria obtained in (i)and optionally (ii), optionally in the presence of a stabiliser and/orcryprotectant. The method may also comprise a step of preparing acapsule, tablet, or enema comprising the bacteria obtained in (i) andoptionally (ii). The capsule or tablet may be enteric-coated, pHdependent, slow-release, and/or gastro-resistant.

The composition of the invention may also be provided in the form of afood supplement, beverage or other food stuff. The invention thus alsorelates to a food product or a vaccine comprising a composition of theinvention.

Also provided is an immunogenic composition comprising fragments ofbacteria selected from the those listed in Table 1, for use as anadjuvant to an anti-PD-1/PD-L1/PD-L2 antibody-based therapy administeredto a cancer patient.

Biomarker

The invention provides microbiome biomarkers that are predictive oftumor response to therapy in a cancer patient with an immune checkpointinhibitor. In particular, the invention provides a microbiome biomarkersignature that is predictive of tumor response therapy with an immunecheckpoint inhibitor. As used herein, a microbiome biomarker signatureis a composite biomarker signature that comprises bacteria from at least2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 bacterial species asshown in Table 1 which each have increased abundance in subjects thatare responsive to therapy with an immune checkpoint inhibitor. In oneembodiment, the signature comprises bacteria from at least 9, 10, 11,12, 13, 14 or 15 bacterial species selected from Table 1 which each haveincreased abundance in a population of subjects that are responsive totherapy with an immune checkpoint inhibitor. The biomarker signature isdescribed in more detail below.

Another aspect provides a method of treating cancer in a subjectcomprising administering a therapeutically effective amount of an immunecheckpoint inhibitor to said subject, wherein the subject has beendetermined to have a favorable microbial profile in the gut microbiome.A favorable microbial profile is characterised by the presence of thebiomarkers/biomarker signature described herein.

Another aspect provides a method of treating cancer in a subject,wherein the subject has been determined to have an unfavorable microbialprofile in the gut microbiome. A unfavorable microbial profile ischaracterised by the absence of the biomarkers/biomarker signaturedescribed herein. The method may further comprise administration of ananti-cancer therapy that is not an immune checkpoint inhibitor therapy.In another embodiment, the method comprises administration of atherapeutic bacterial composition described herein and co-therapy withan immune checkpoint inhibitor therapy, e.g. a PD-1 inhibitor.

Thus, the invention also relates to a method for identifying a subjectthat will respond to therapy with an immune checkpoint inhibitor, e.g.PD-1, comprising determining the abundance of one or more of thebacteria identified as B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11,B12, B13, B14 and/or B15 in Table 1 in a biological sample from saidsubject that comprises gut (i.e. intestinal) flora wherein an increasein the abundance of one or more of B1, B2, B3, B4, B5, B8, B7, B8, B9,B10, B11, B12, B13, B14 and/or B15, e.g. one or more of B1, B2, B3, B4,B5, B8, B7, B8 and/or B9, is indicative that the subject will respond totherapy with an immune checkpoint inhibitor, e.g. PD-1. B1 to B15 arelisted in Table 1 and this includes references to sequence identifiersto define the bacteria. Corresponding sequences are listed in Table 2.In one embodiment, the subject is a patient that has been diagnosed witha cancer, e.g. melanoma.

In particular, the invention also relates to a method for predicting aresponse to an immune checkpoint inhibitor therapy in a subject havingcancer/a method for identifying a subject that will respond to therapywith an immune checkpoint inhibitor, the method comprising:

a) determining the abundance of one or more of the bacteria selectedfrom B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14 and/orB15 in Table 1 in a biological sample obtained from the subject and

b) comparing the abundance to a reference level from cancer patientsthat do not respond to therapy with an immune checkpoint inhibitor; orcomparing the abundance to a reference level from cancer patients thatrespond to therapy with an immune checkpoint inhibitor;

wherein if the reference level is from cancer patients that do notrespond to therapy with an immune checkpoint inhibitor, then an increasein the abundance of one or more of B1, B2, B3, B4, B5, B6, B7, B8, B9,B10, B11, B12, B13, B14 and/or B15 compared to the reference level, isindicative that the subject will respond to therapy with an immunecheckpoint inhibitor or

wherein if the reference level is from patients that do respond totherapy with an immune checkpoint inhibitor, then the same,substantially the same or an increase in the abundance of one or more ofB1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14 and/or B15,is indicative that the subject will respond to therapy with an immunecheckpoint inhibitor.

An additional step may include identifying the subject that will respondto therapy.

In particular, the invention also relates to a method for predicting aresponse to an immune checkpoint inhibitor therapy in a subject havingcancer/a method for identifying a subject that will respond to therapywith an immune checkpoint inhibitor, the method comprising:

a) determining the abundance of one or more of the bacteria selectedfrom B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14 and/orB15 in Table 1 in a biological sample obtained from the subject and;

b) comparing the abundance to a reference level from cancer patients orhealthy subjects and

c) applying random forest analysis. In this embodiment, the referencelevel is from cancer patients, that is a pool of cancer patients. Thesemay include responders and non-responders.

An additional step may include identifying the subject that will respondto therapy or prediction a response.

Thus, the abundance of bacteria from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14 or 15 different species selected from B1, B2, B3, B4, B5, B6,B7, B8, B9, B10, B11, B12, B13, B14 and B15 in Table 1 is determined.Respective sequences characterising the species are provided as SEQ IDs1 to 15. As explained elsewhere, SEQ IDs 16-29 can also be used. In someembodiments, the abundance of bacteria selected from at least 9, 10, 11,12, 13, 14 or 15 different species identified as B1, B2, B3, B4, B5, B6,B7, B8, B9, B10, B11, B12, B13, B14 and B15 in Table 1 is determined.Thus, the abundance of bacteria having sequences IDs selected from atleast 9 of the following SEQ IDs is determined: SEQ ID NO. 1, 2, 3, 4,5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 or sequences with at least 97%,98%, 98.7% or 99% sequence identity thereto, such as, for example SEQIDs 16 to 29.

Also provided is a method for predicting relapse in a patient who istreated or who has been treated for a cancer, comprising assessing, infaeces samples from said patient obtained e.g. at different time-points,the presence/relative abundance of one or more bacteria selected fromB1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14 and/or B15.

When abundance is determined, an abundance score is obtained for each ofthe bacteria, i.e. bacterial species, and measured. According to themethod, an increase in the abundance, i.e. the abundance score, of oneor more of the bacteria listed in Table 1 is indicative that the subjectwill respond to therapy with an immune checkpoint inhibitor. An increaserefers to an increase of abundance, i.e. the abundance score, comparedto a reference value. Therefore, the method may also comprise comparingthe abundance one or more of the bacteria listed in Table 1 to one ormore reference value. For example, the abundance of one or more of thebacteria listed in Table 1 can be compared to a reference value for oneor more of the bacteria listed in Table 1. Alternatively, the arithmeticmean of the abundance of one or more of the bacteria listed in Table 1can be compared to a single reference value which is the referencearithmetic mean of the abundance of one or more of the bacteria listedin Table 1. In one embodiment, the method determines the abundance of atleast 9, 10, 11, 12, 13, 14 or 15 different bacteria selected from B1 toB15, thus determining a microbiome biomarker signature, i.e. amicrobiome biomarker signature score, that is based on the compositesignature.

In one embodiment of the methods, the abundance of all of the bacterialisted in Table 1 is determined. In another embodiment, the abundance ofa subset the bacteria listed in Table 1 is determined. For example, thesubset comprises or consists of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14 or 15 different bacteria selected from Table 1. In oneembodiment, the subset comprises or consists of 9 bacteria, e.g.Eisenbergiella sp., Butyriccoccus sp., Closbidiales sp., Alistipesobesi, Alistipes indistinctus, Gordonibacter urolithinfaciens,Faecalitalea sp., Blauti sp. (B8), and Barnesiella intestinihominis. Inone embodiment, the subset comprises or consists of 9 or 12 bacteria,e.g. one of the bacterial consortia in Table 3. In one embodiment, thebiomarker does not comprise an Alistipes species.

The reference value may be a predetermined value from a referencesample. For example, the reference value can be the average abundance ofeach of the bacteria or their composite signature, respectively, in apool of reference subjects.

For example, the reference value is a predetermined value, e.g. apredetermined threshold value. Such a value can be predetermined from areference sample. A predetermined threshold value relating to abundanceof one or more bacteria of B1 to B15 refers to the abundance of thebacteria in the sample as a proportion of the total microbiota in thesample, for example a stool sample, above or below which the sample isscored as being positive for the signature and thus responsive totherapy with an immune checkpoint inhibitor. For example, if theabundance score for the test sample is at or above a predeterminedthreshold, then the sample is considered to be positive for thesignature and the subject is responsive to therapy with an immunecheckpoint inhibitor.

For example, abundance scores of the tested bacteria levels in a samplepool are stored on a computer, or on computer-readable media, to be usedas reference levels in comparisons to the abundance of the testedbacteria from the test sample when needed. Machine learning algorithmsand/or models commonly used in the identification of biomarkers, such asa Cox model, trained using training data comprising information on aplurality of biomarkers in a set of subjects or other models may be usedto establish reference values and or to correlate abundance of thebacteria selected from one or more of the bacteria listed in Table 1 inthe sample with the subject's responsiveness to treatment with an immunecheckpoint inhibitor.

The term “correlating” is used herein to determine or calculateresponsiveness to treatment status based on modulated abundance of oneor more bacteria should be understood to mean any methods ofcorrelation, e.g. algorithmic methods. The methodology described hereinemploys a mathematical modelling technique known as Random ForestClassification, but other modelling techniques may be employed.Therefore, in one embodiment, a Random Forest Classification Model orsimilar model is used to correlate abundance of the bacteria selectedfrom one or more of the bacteria listed in Table 1 in the sample withthe subject's responsiveness to treatment with an immune checkpointinhibitor. Thus, in one embodiment, the methods of the invention mayemploy a computer program to correlate modulated abundance of thebacteria with immune checkpoint inhibitor treatment response.

Alternatively, the reference value is not predetermined, but it isestablished as part of a single experiment. Thus, the abundance of theone or more tested bacteria in the test sample may be compared to theabundance of the one or more tested bacteria in the pool of samples,where abundance of the tested bacteria from the test sample andabundance of the tested bacteria from the pool are determined during thecourse of a single experiment.

In the various embodiments, the reference sample/sample pool may be apopulation of cancer patients that have been shown to be responsive ornon-responsive to therapy with an immune checkpoint inhibitor. In otherembodiments, the reference sample/sample pool may be a population ofcancer patients that have not yet received therapy with a checkpointinhibitor.

In one embodiment, the reference sample used to establish a referencevalue may be from non-responders to immune checkpoint inhibitor therapy.If the test sample shows an increased abundance of the one or morebacteria selected from B1 to B15 compared to the reference sample, thenthe test subject is likely to respond to therapy with a checkpointimmune inhibitor. The increase may be at least 10%, 20%, 30%, 40%, 50%,60%, 70%, 80%, 90% or more.

In one embodiment, the reference sample used to establish a referencevalue may be from responders to immune checkpoint inhibitor therapy. Ifthe test sample shows the same, substantially the same or an increase inthe abundance of the one or more bacteria selected from B1 to B15 thanthe reference sample, then the test subject is likely to respond totherapy with a checkpoint immune inhibitor.

As a skilled person would understand, a reference value or referencegene signature score as used herein means the score for a bacterialabundance signature that has been determined to divide at least themajority of responders from at least the majority of non-responders in areference population of subjects.

As used herein, a “good responder to a treatment”, also called a“responder” or “responsive” patient or in other words a patient who“benefits from” this treatment, refers to a patient who is affected witha cancer and who shows or will show a clinically significant relief inthe cancer after receiving this treatment. Conversely, a “bad responder”or “non-responder” is one who does not or will not show a clinicallysignificant relief in the cancer after receiving this treatment. Theresponse to treatment may be assessed according to the standardsrecognized in the art, such as immune-related response criteria (irRC),WHO or RECIST criteria.

A signature biomarker described herein is useful to identify cancerpatients who are most likely to achieve a clinical benefit fromtreatment with an immune checkpoint inhibitor. This utility supports theuse of these biomarkers in a variety of research and commercialapplications. Including but not limited to, clinical trials of PD-1antagonists in which patients are selected on the basis of theirmicrobiome gene signature score, diagnostic methods and products fordetermining a patients microbiome gene signature score or forclassifying a patient as positive or negative for a microbiome signaturebiomarker, personalized treatment methods which involve tailoring apatient's drug therapy based on the patient's microbiome signaturescore, as well as pharmaceutical compositions and drug productscomprising a PD-1 antagonist for use in treating patients who testpositive for a microbiome signature biomarker.

A skilled person would also understand that the utility of any of theapplications claimed herein does not require that 100% of the patientswho test positive for a biomarker of the invention achieve an anti-tumorresponse to an immune checkpoint inhibitor, nor does it require adiagnostic method or kit to have a specific degree of specificity orsensitivity in determining the presence or absence of a biomarker inevery subject, nor does it require that a diagnostic method claimedherein be 100% accurate in predicting for every subject whether thesubject is likely to have a beneficial response to a PD-1 antagonist.Thus, the inventors herein intend that the terms “determine”,“determining” and “predicting” should not be interpreted as requiring adefinite or certain result; instead these terms should be construed asmeaning either that a claimed method provides an accurate result for atleast the majority of subjects or that the result or prediction for anygiven subject is more likely to be correct than incorrect. Preferably,the accuracy of the result provided by a diagnostic method of theinvention is one that a skilled artisan or regulatory authority wouldconsider suitable for the particular application in which the method isused.

As used herein, the sample is a biological sample from the gut, i.e. onethat comprises gut intestinal flora. This refers to a sample obtainedfrom the gut of a subject, for example a faecal sample. Methods ofisolating bacteria from a faecal sample are known. In some cases, themicrobiome sample is obtained by mucosal biopsy. A test sample is sampleobtained from a subject that is being assessed.

In one embodiment of the method, the abundance is relative abundance. Asused herein, the term “relative abundance” as applied to a bacterium ina sample should be understood to mean the abundance of the bacterium inthe sample as a proportion of the total microbiota in the sample or areference sample. In one embodiment, the relative abundance is theabundance of the bacterium in the sample as a proportion of the totalmicrobiota in the sample.

In one embodiment, the modulated abundance is a difference in relativeabundance of the bacterium in the sample compared with the relativeabundance in the same sample from a reference subject.

In one embodiment, the abundance of the bacterium in the sample as aproportion of the total microbiota in the sample is measured todetermine the relative abundance of the bacterium. Then, in suchembodiments, the relative abundance of the bacterium in the sample iscompared with the relative abundance in the same sample from a referenceindividual (also referred to herein as the “reference relativeabundance”). A difference in relative abundance of the bacterium in thesample, e.g. an increase, compared to the reference relative abundanceis a modulated relative abundance. Detection of modulated abundance canalso be performed in an absolute manner by comparing sample abundancevalues with absolute reference values.

Any suitable method of detecting bacterial presence/abundance may beemployed, including, for example, agar plate quantification assays,fluorimetric sample quantification, PCR methods, 16S rRNA/rDNA geneamplicon sequencing, Shotgun metagenomic sequencing and dye-basedmetabolite depletion or metabolite production assays. The PCR techniqueused can quantitatively measure starting amounts of DNA, cDNA, or RNA.Examples of PCR-based techniques according to the invention includetechniques such as, but not limited to, quantitative PCR (Q-PCR),reverse-transcrdptase polymerase chain reaction (RT-PCR), quantitativereverse-transcriptase PCR (QRT-PCR), rolling circle amplification (RCA)or digital PCR. These techniques are well known and easily available anddo not need a precise description. In a particular embodiment, thedetermination of the copy number of the bacterial genes of the inventionis performed by quantitative PCR.

In one embodiment, the sample is analysed using a nucleic acidamplification reaction. Analysing may include detecting family, order-,class- and/or genus-specific 16S rRNA/rDNA or other sequences in thebacterial genome. In one embodiment, full length 16S rDNA may bedetected. In one embodiment, partial 16S rDNA may be detected, forexample one of the V regions. In one embodiment, analysing includeshybridizing bacterial nucleic acid in the sample to beads or to anarray, e.g. a nucleic acid microarray.

The PCR-based techniques are performed with amplification primersdesigned to be specific for the sequences which are measured. Thepresent invention hence also pertains to a set of primers suitable forperforming the above method, i.e., a set of primers comprising primerpairs for amplifying sequences specific for each of the microorganismspecies to be detected (i.e., at least one more species selected amongstthose recited in Tables 1 and 2 and 3).

16S rDNA sequence is provided herein for B1-B15 and this can be used togenerate primers for such an analysis. In one embodiment, a plurality ofthe bacteria is detected. In one embodiment, the sample is analysed fornucleic acid of the bacteria using genome sequencing.

In one embodiment, the subject is a cancer patient, such as melanomapatient. The cancer patient may or may not have received anti-cancertreatment. Thus, the subject may be one that is in need of treatmentwith an immune checkpoint inhibitor. In one embodiment, the subject is ahealthy individual, for example a healthy individual with a familyhistory of cancer, such as melanoma.

In one embodiment, if the subject is a cancer patient and has beenidentified as a subject that will respond to therapy with an immunecheckpoint inhibitor, then the method may include the further step ofadministering an immune checkpoint inhibitor to said patient.

In one embodiment, the method also comprises the prior step of obtainingthe biological sample that comprises gut flora.

In one embodiment, the method also includes the initial step ofidentifying a subject in need of treatment with the immune checkpointinhibitor.

In one embodiment of the methods, if the subject is identified as aresponder, e.g. If one or more of the bacteria listed in Table 1 hasbeen shown to have an increased abundance in the sample, an anti-cancertherapy comprising an immune checkpoint inhibitor is administered to thesubject.

Checkpoint inhibitors are as defined herein. In one embodiment of themethods, the immune checkpoint inhibitor inhibits PD-1 activity, i.e.acts as a PD-1 antagonist. In one embodiment of the methods, the immunecheckpoint inhibitor inhibits PD-L1 activity, i.e. acts as a PD-L1antagonist. In one embodiment of the methods, the immune checkpointinhibitor inhibits CTLA-4 activity, i.e. acts as a CTLA-4 antagonist. Inone embodiment of the methods, the immune checkpoint inhibitor inhibitsLAG3, TIGIT or TIM3-activity.

In one embodiment the immune checkpoint inhibitor is an anti PD-1, PD-L1or CTLA-4 antibody. In one embodiment, the anti PD-1 antibody isselected from nivolumab, pembrolizumab, cemiplimab, avelumab,durvalumab, atezolizumab, Spartalizumab, Camrelizumab, Sintilimab,Tislelizumab, Pidilizumab or Toripalimab, Ipilimumab or Tremelimumab.

In one embodiment, the immune checkpoint inhibitor is an interferingnucleic acid molecule. In one embodiment, the interfering nucleic acidmolecule is an siRNA molecule, an shRNA molecule or an antisense RNAmolecule.

In one embodiment, the immune checkpoint inhibitor is a small moleculeor PROteolysis TArgeting Chimera (PROTAC) or another immune checkpointinhibitor as defined above.

In one embodiment, in a further step of the method, surgical, radiation,and/or chemotherapeutic cancer intervention is carried out or a secondanti-cancer therapeutic is administered to said subject.

In another aspect, the invention relates to a method of detecting therisk that a subject will not respond to therapy with an immunecheckpoint inhibitor. The method comprising determining the abundance ofone or more of the bacteria listed in Table 1 in a biological samplefrom said subject that comprises gut intestinal flora wherein a decreasein the abundance or an abundance below a reference level of one or moreof the bacteria listed in Table 1 is indicative that the subject willnot respond to therapy with an immune checkpoint inhibitor. The methodmay also comprise comparing the abundance of one or more of the bacterialisted in Table 1 to one or more reference value. A reference value isas described above. The abundance that is determined is relativeabundance. In a further step, if the subject has been identified as asubject that will not respond to therapy with an immune checkpointinhibitor, alternative anti-cancer treatment is administered.Alternatively, in a further step, if the subject has been identified asa subject that will not respond to therapy with an immune checkpointinhibitor, a therapeutic bacterial composition as described herein isadministered together with a checkpoint inhibitor therapy, e.g. an antiPD-1 therapy.

In another aspect, the invention relates to a method of discriminatingbetween subjects that respond to therapy with an immune checkpointinhibitor and subjects that do not respond to therapy with an immunecheckpoint inhibitor. The method comprising determining the abundance ofone or more of the bacteria listed in Table 1 in a biological samplefrom said subject that comprises gut intestinal flora wherein a decreasein the abundance or a abundance below a reference level of one or moreof the bacteria listed in Table 1 is indicative that the subject willnot respond to therapy with an immune checkpoint inhibitor and anincrease in the abundance of one or more of the bacteria listed in Table1 is indicative that the subject will respond to therapy with an immunecheckpoint inhibitor. The method may also comprise comparing theabundance one or more of the bacteria fisted in Table 1 to one or morereference value. A reference value is as described above. The abundancethat is determined is relative abundance. In a further step, if thesubject has been identified as a subject that will not respond totherapy with an immune checkpoint inhibitor, alternative anti-cancertreatment is administered.

In one embodiment of the biomarker methods above, modulated abundance ofat least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 differentbacteria selected from Table 1 is indicative of a response to treatment.In another embodiment of the biomarker methods above, modulatedabundance of at least 9, 10, 11, 12, 13, 14 or 15 different bacteriaselected from Table 1 is indicative of a response to treatment. Thus,establishing a composite signature that includes abundance of at least9, 10, 11, 12, 13, 14 or 15 different bacteria is a particularembodiment of the methods. It is the totality of the bacteria, i.e. thebiomarker signature, that provides a particularly powerfuldiscriminatory tool.

In one embodiment of the various methods above, the abundance of atleast 9 bacterial species/a population of 9 bacterial species selectedfrom those in Table 1 is assessed, i.e. 9 species selected from SEQ IDNos. 1, 2, 3, 4, 5 6, 7, 8, 9, 10, 11, 12, 13, 14 and 15. In oneembodiment, the subset of 9 corresponds to a consortium as shown inTable 3, i.e. consortia 2, 4, 5, 6 or 10. In one embodiment, the 9species comprise bacteria as defined by SEQ ID NO. 1 or a sequence withat least 97%, 98%, 98.7% or 99% sequence identity thereto. In oneembodiment, the 9 species comprise bacteria as defined by SEQ ID NO. 2or a sequence with at least 97%, 98%, 98.7% or 99% sequence identitythereto. =In one embodiment, the 9 species comprise bacteria as definedby SEQ ID NO. 3 or a sequence with at least 97%, 98%, 98.7% or 99%sequence identity thereto. In one embodiment, the 9 species comprisesbacteria as defined by SEQ ID NO. 4 or a sequence with at least 97%,98%, 98.7% or 99% sequence identity thereto. In one embodiment, the 9species comprise bacteria as defined by SEQ ID NO. 5 or a sequence withat least 97%, 98%, 98.7% or 99% sequence identity thereto. In oneembodiment, the 9 species comprise bacteria as defined by SEQ ID NO. 6or a sequence with at least 97%, 98%, 98.7% or 99% sequence identitythereto. In one embodiment, the 9 species comprise bacteria as definedby SEQ ID NO. 7 or a sequence with at least 97%, 98%, 98.7% or 99%sequence identity thereto. In one embodiment, the 9 species comprisebacteria as defined by SEQ ID NO. 8 or a sequence with at least 97%,98%, 98.7% or 99% sequence identity thereto. In one embodiment, the 9species comprise bacteria as defined by SEQ ID NO. 9 or a sequence withat least 97%. 98%, 98.7% or 99% sequence identity thereto. In oneembodiment, the 9 species comprise bacteria as defined by SEQ ID NO. 10or a sequence with at least 97%, 98%, 98.7% or 99% sequence identitythereto. In one embodiment, the 9 species comprise bacteria as definedby SEQ ID NO. 11 or a sequence with at least 97%, 98%, 98.7% or 99%sequence identity thereto. In one embodiment, the 9 species comprisebacteria as defined by SEQ ID NO. 12 or a sequence with at least 97%,98%, 98.7% or 99% sequence identity thereto. In one embodiment, the 9species comprise bacteria as defined by SEQ ID NO. 13 or a sequence withat least 97%, 98%, 98.7% or 99% sequence identity thereto. In oneembodiment, the 9 species comprise bacteria as defined by SEQ ID NO. 14or a sequence with at least 97%, 98%, 98.7% or 99% sequence identitythereto. In one embodiment, the 9 species comprise bacteria as definedby SEQ ID NO. 15 or a sequence with at least 97%, 98%, 98.7% or 99%sequence identity thereto. In one embodiment, the 9 species do notcomprise an Alistipes species.

In one embodiment, the biomarker methods above may comprise a furtherstep of determining another biomarker that is predictive of tumorresponse with an immune checkpoint inhibitor, for example a PD-1, PD-L1or CTLA-4 antagonist. For example, the biomarker may be a ProgrammedDeath Ligand 1 (PD-L1) or Programmed Death Ligand 1 (PD-L2) genesignature. Thus, the method may comprise the step of obtaining a samplefrom the tumor of a test subject, measuring RNA expression level in thetumor sample of one or more gene in a PD-1 and/or PD-L1 gene signatureand comparing the RNA expression level to a reference level. Expressioncan be measured by any appropriate methods, includingimmunohistochemistry.

In another aspect, the invention relates to one or more of the bacterialisted in Table 1 for use as a predictive biomarker in determining theefficacy of therapeutic intervention with checkpoint inhibitor, e.g.PD-1 therapy. The term predictive biomarker as used herein is todescribe a biomarker that gives information about the effect of atherapeutic intervention, i.e. responsiveness to treatment with animmune checkpoint inhibitor. Thus, the invention also relates to the useof one or more bacterium: e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14 or 15 different bacteria selected from one or more of thebacterial species listed in Table 1 in identifying a patient that willrespond to therapy with an immune checkpoint inhibitor.

The invention also relates to a biomarker signature, that is aconsortium of one or more of the bacteria listed in Table 1, e.g. as inTable 3, which can be used to predict the efficacy of therapeuticintervention with checkpoint inhibitor therapy, e.g. with a PD-1inhibitor or with another checkpoint inhibitor therapy.

Systems and Computer Readable Media

Embodiments of the invention also provide for systems (and computerreadable media for causing computer systems) to perform a method fordetermining responsiveness to treatment with an immune checkpointinhibitor in a subject. In another aspect, a computer-implemented methodis provided for indicating a likelihood that a subject responds totreatment with an immune checkpoint inhibitor. The method comprises:retrieving on a computer biomarker information for an individual,wherein the biomarker information comprises biomarker values that eachcorrespond to the abundance of one or more bacteria selected from thegroup of bacteria set forth in Table 1; performing with the computer aclassification of each of the biomarker values; and indicating alikelihood that the subject responds to treatment with an immunecheckpoint inhibitor based upon a plurality of classifications.

In another aspect, a computer program product is provided for indicatinga likelihood that a subject responds to treatment with an immunecheckpoint inhibitor. The computer program product includes a computerreadable medium embodying program code executable by a processor of acomputing device or system, the program code comprising: code thatretrieves data attributed to a biological sample from an individual,wherein the data comprises biomarker values that each correspond to theabundance of one or more bacteria selected from the group of bacteriaset forth in Table 1; and code that executes a classification methodthat indicates a likelihood that the individual responds to treatmentwith an immune checkpoint inhibitor as a function of the biomarkervalues.

In one embodiment the reference data stored in the storage device to beread by the comparison module is compared, e.g., relative abundance of aparticular bacterium in a reference sample as described herein. The“comparison module” can use a variety of available software programs andformats for the comparison operative to compare bacteria abundanceinformation data determined in the determination system to referencesamples and/or stored reference data, e.g. a predetermined thresholdvalue. In one embodiment, the comparison module is configured to usepattern recognition techniques to compare information from one or moreentries to one or more reference data patterns. The comparison modulemay be configured using existing commercially-available orfreely-available software for comparing patterns and may be optimizedfor particular data comparisons that are conducted. The comparisonmodule provides computer readable information related to theresponse-associated bacteria.

The comparison module provides a computer readable comparison resultthat can be processed in computer readable form by predefined criteria,or criteria defined by a user, to provide a content based in part on thecomparison result that may be stored and output.

The methods described herein therefore provide for systems (and computerreadable media for causing computer systems) to perform methods fordetermining responsiveness to treatment with an immune checkpointinhibitor in a subject.

FMT

Implantation or administration of human microbiota into the bowel of asick patient is called Faecal Microbiota Transplantation (FMT), alsocommonly known as faecal bacteriotherapy. FMT is believed to repopulatethe gut with a diverse array of microbes that bring missing beneficialfunctions or microbiota to the resident gut bacteria, displace harmfulmicrobiota or control key pathogens by creating an unfavourableecological environment.

In another aspect, the invention relates to a method forscreening/identifying a faecal donor comprising assessing a faecalsample of a subject for the presence of one or more bacteria associatedwith response to cancer; e.g. response to cancer when a patient istreated with an immune checkpoint inhibitor and identifying the faecaldonor based on the presence and/or abundance of one or more bacteria.

For example, in such a method, the one or more bacteria selected fromTable 1 and the faecal donor is identified based on the presence and/orabundance of one or more bacteria selected from Table 1.

In another aspect, the invention relates to a method forscreening/identifying a faecal donor comprising assessing a faecalsample of a subject for the presence of one or more bacteria selectedfrom Table 1 and identifying the faecal donor based on the presenceand/or abundance of one or more bacteria selected from Table 1. Themethod may also comprise obtaining a faecal sample from a donor.Assessing a faecal sample of a subject for the presence of one or morebacteria can be done by methods known in the art, e.g. sequence analysisof bacterial genomes, e.g. using a shotgun sequencing approach. Forexample, one or more of the bacteria is present above a predeterminedthreshold, the donor is selected as a donor for bacteriotherapypurposes. The predetermined threshold may be based on the averageabundance of the one or more bacteria in faecal samples obtained from adonor population. A higher than average abundance indicates that thefaeces are suitable for FMT therapy.

The invention also relates to a use of one or more bacteria selectedfrom Table 1 in a method for identifying a donor for FMT therapy.

The invention relates to a method for treating a faecal transplant priorto administration to a subject comprising supplementing the faecaltransplant with one or more bacterial isolates selected from Table 1 orwith a faecal sample obtained from a donor by the method describedabove.

According to another aspect of the present invention, an individual inneed of a treatment with an immune checkpoint inhibitor therapy istreated by FMT, using faecal microbiota from healthy individual(s) thathas been shown to be abundant in one or more of the species in table 1,and/or faecal microbiota from one or several individual(s) treated withan immune checkpoint inhibitor therapy and who proved to respond to thistherapy, and/or faecal microbiota from one or several individual(s)exhibiting a gut microbiota profile that identifies him/her/them aslikely to respond to the envisioned treatment or from a respondingpatient.

In the aspects above, the FMT therapy is for the treatment of a diseaseas mentioned herein, e.g. a cancer such as melanoma.

Composition and Methods for Increasing Abundance of Bacteria in a Host

In another aspect of the invention, a subject's microbiome may bealtered to increase the abundance of bacteria listed in Table 1 or asubset thereof. Glycan metabolism has been shown to influence the humangut microbiota and prebiotics can enrich bacterial taxa that promoteanti-tumor immunity (Koropatkin et al, Nature Reviews Microbiologyvolume 10, pages 323-335 (2012); Li et al, Cell Report, Volume 30. ISSUE6, P1753-1766.e6, Feb. 11, 2020). Thus, there is provided a method forincreasing the abundance of bacteria listed in table 1 in a subject or asubset thereof by administration of a composition comprisingoligosaccharides, such as glycans. Compositions comprisingoligosaccharides, such as glycans for use in such a method are alsoenvisaged.

Kits

In a further aspect, the invention relates to a kit. The kit includes acomposition described herein and optionally an anti-cancer treatmentthat includes an immune checkpoint inhibitor as described herein. In anexample, the kit can include materials to ship the collected materialwithout harming the samples (e.g., packaged in lyophilized form, orpackaged in an aqueous medium etc.). The kit may include the processedmaterial or treatment in a sterile container, such as a nasogastric (NG)tube, a vial (e.g., for use with a retention enema), a gastro-resistantcapsule (e.g., acid-bio resistant to reach the intestinal tract, havinga sterile outside), etc. The kit may also comprise instructions for use.

In an alternative aspect, the kit comprises

-   -   a sealable container configured to receive a biological sample,        such as a faecal sample;    -   polynucleotide primers for amplifying a 16S rDNA polynucleotide        sequence from at least one gut associated bacterium to form an        amplified 16S rDNA polynucleotide sequence, wherein the        amplified 16S rDNA sequence has at least 97%, 98%, 98.7% or 99%        homology to a polynucleotide sequence selected from SEQ ID NOs 1        to SEQ ID NO 15, e.g. SEQ ID NOs 16 to 29;    -   a detecting reagent to detect the amplified 16S rDNA sequence;        and    -   instructions for use.

The invention also relates to as kit comprising a composition comprisingoligosaccharides, such as glycans for use in a method for increasing theabundance of bacteria listed in table 1 in a subject or a subset thereofby administration of the composition.

The invention also relates to the use of a composition of the invention,i.e. comprising or consisting of one or more a bacterial isolate asshown in Table 1 with reference to a SEQ ID NO. shown therein, inincreasing efficacy of an anti-cancer treatment with an immunecheckpoint inhibitor. The invention also relates to the use of acomposition of the invention, i.e. comprising or consisting of one ormore a bacterial isolate as shown in Table 1 with reference to a SEQ IDNO. as shown in the Table, in enhancing immune checkpoint blockade. Theinvention also relates to a method for increasing efficacy of ananti-cancer treatment with an immune checkpoint inhibitor comprisingadministering a composition of the invention, i.e. comprising orconsisting of one or more bacterial isolate as shown in Table 1 withreference to a SEQ ID NO., to a subject. The invention also relates to amethod for enhancing immune checkpoint blockade comprisingadministration of a composition of the invention, i.e. comprising orconsisting of one or more bacterial isolate as shown in Table 1 withreference to a SEQ ID NO. as shown in the Table to a subject.

The invention also relates to the use of a composition of the inventionin providing an immunostimulatory effect.

The invention also relates to a method for determining if a cancerpatient needs a bacterial composition of the invention, i.e. comprisingor consisting of one or more a bacterial isolate as shown in Table 1with reference to a SEQ ID NO. as shown therein, before administrationof an immune checkpoint inhibitor comprising assessing, in a faecessample from said patient, the presence or absence or one or morebacterial isolates selected from the species in Table 1.

Aspects

The invention is further described in the following aspects.

-   -   1. A composition comprising isolated bacteria selected from at        least two species wherein the bacteria from the first species        comprise a 16S rDNA sequence having at least 98.7% sequence        identity with a nucleic acid sequence according to SEQ ID NO: 1,        and the bacteria from the second species comprise a 16S rDNA        sequence having at least 98.7% sequence identity with a nucleic        acid sequence according to SEQ ID NO: 2.    -   2. The composition according to aspect 1, further comprising        isolated bacteria from at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,        11, 12 or 13 different species wherein the bacteria comprise a        16S rDNA sequence selected from a sequence having at least 98.7%        sequence identity with a nucleic acid sequence according to SEQ        ID NO: 3 to 15.    -   3. The composition according to aspect 1 further comprising        isolated bacteria from at least 4 different species wherein the        bacteria comprise a 16S rDNA sequence selected from a sequence        having at least 98.7% sequence identity with a nucleic acid        sequence according to SEQ ID NO: 3 to 15.    -   4. The composition according to aspect 1, further comprising        isolated bacteria from at least 7 different species wherein the        bacteria comprise a 16S rDNA sequence selected from a sequence        having at least 98.7% sequence identity with a nucleic acid        sequence according to SEQ ID NO: 3 to 15.    -   5. The composition according to aspect 1, further comprising a        bacterial isolate comprising a 168S rDNA sequence selected from        a sequence having at least 98.7% sequence identity with a        nucleic acid sequence according to SEQ ID NO: 7.    -   6. The composition according to aspect 1 comprising a consortium        selected from consortia 1 to 4 or 6 to 10 as shown in Table 3.    -   7. The composition according to any preceding aspect, wherein        said composition is formulated for oral or rectal        administration.    -   8. The composition according to aspect 7, wherein said        composition is in the form of a capsule, tablet, gel or liquid.    -   9. The composition according to aspect 8, wherein said        composition is encapsulated in an enteric coating.    -   10. The composition according to any preceding aspect, wherein        the composition comprises live, attenuated or killed bacteria.    -   11. The composition according to any preceding aspect, wherein        the composition comprises bacterial spores.    -   12. The composition according to any of aspects 1 to 11, wherein        the composition does not comprise bacterial spores.    -   13. The composition according to any preceding aspect, wherein        the composition comprises bacterial strains that originate from        one or more human donor.    -   14. The composition according to any preceding aspect, wherein        the bacteria are lyophilized.    -   15. The composition according to any preceding aspect, wherein        the composition comprises at least about 1×10³ to 1×10¹³ CFU of        bacteria.    -   16. The composition according to any preceding aspect, wherein        administration of the composition induces an immune response in        a subject and/or increases the efficacy of an anti cancer        therapy that includes an immune checkpoint inhibitor.    -   17. A pharmaceutical composition comprising a composition of any        of aspects 1 to 16 and a pharmaceutical carrier.    -   18. The pharmaceutical composition according to aspect 17,        further comprising an effective amount of an immune checkpoint        inhibitor or a vaccine.    -   19. The pharmaceutical composition according to aspect 18,        wherein the immune checkpoint inhibitor inhibits PD-1, PDL-1,        CTLA-4, LAG3 or TIM-3 activity.    -   20. The pharmaceutical composition according to aspect 19        wherein the immune checkpoint inhibitor is an anti PD-1, PDL-1        or CTLA-4 antibody or fragment thereof.    -   21. The pharmaceutical composition according to aspect 20        wherein the anti PD-1, PDL-1 or CTLA4 antibody is selected from        nivolumab, pembrolizumab, cemiplimab, avelumab, durvalumab,        atezolizumab, spartalizumab, camrelizumab, sintilimab,        tislelizumab, pidilizumab toripalimab, Ipilimumab or        Tremelimumab.    -   22. The pharmaceutical composition according to aspect 18,        wherein the immune checkpoint inhibitor is an interfering        nucleic acid molecule, a small molecule or PROteolysis TArgeting        Chimera (PROTAC), alternative protein scaffold or other immune        checkpoint inhibitor.    -   23. The pharmaceutical composition according to aspect 22,        wherein the interfering nucleic acid molecule is an siRNA        molecule, an shRNA molecule or an antisense RNA molecule.    -   24. A composition according to any of aspects 1 to 16, or a        pharmaceutical composition of any of aspects 17 to 23 for use in        the treatment of disease.    -   25. A composition according to any of aspects 1 to 16, or a        pharmaceutical composition of any of aspects 17 to 23 for use in        the treatment of cancer or an infectious disease or for use as a        vaccine adjuvant or for increasing the efficacy of a cancer        treatment.    -   26. A method for treating cancer or an infectious disease in a        subject in need thereof, comprising administering a composition        according to any of aspects 1 to 17 or a pharmaceutical        composition of aspect 17, to said subject.    -   27. The method of aspect 26 wherein said subject is receiving,        has received or will receive therapy with an immune checkpoint        inhibitor, thereby treating the cancer or infectious disease.    -   28. A method for treating cancer in a subject in need thereof        comprising administering a composition according to aspect 18 to        said subject.    -   29. The method according to aspect 26 or 27, wherein        administration of the composition enhances an immune response by        the subject and/or inhibits immune evasion by the cancer and/or        increases efficacy of an anti cancer treatment with an immune        checkpoint inhibitor.    -   30. The composition for use according to aspect 25, or the        method according to any of aspects 26 to 29 wherein the cancer        is selected from melanoma melanoma, such as Harding-Passey        melanoma, juvenile melanoma, lentigo maligna melanoma, malignant        melanoma, acral-lentiginous melanoma, amelanotic melanoma,        benign juvenile melanoma, Cloudman's melanoma, S91 melanoma,        nodular melanoma, subungual melanoma, Cutaneous melanoma,        uveal/intraocular melanoma and superficial spreading melanoma or        bone cancer, pancreatic cancer, skin cancer, cancer of the head        or neck, cutaneous or intraocular malignant melanoma, uterine        cancer, ovarian cancer, rectal cancer, cancer of the anal        region, stomach cancer, testicular cancer, breast cancer, brain        cancer, carcinoma of the fallopian tubes, carcinoma of the        endometrium, carcinoma of the cervix, carcinoma of the vagina,        carcinoma of the vulva, cancer of the esophagus, cancer of the        small intestine, cancer of the endocrine system, cancer of the        thyroid gland, cancer of the parathyroid gland, cancer of the        adrenal gland, kidney cancer, sarcoma of soft tissue, cancer of        the urethra, cancer of the bladder, renal cancer, lung cancer,        non-small cell lung cancer, thymoma, urothelial carcinoma        leukemia, prostate cancer, mesothelioma, adrenocortical        carcinoma, lymphomas, such as such as Hodgkin's disease,        non-Hodgkin's, gastric cancer, and multiple myelomas.    -   31. The composition for use according to aspect 25 or the method        according to any of aspects 26 to 29, wherein the composition or        pharmaceutical composition is administered by oral        administration or rectal administration.    -   32. The composition for use according to aspect 25 or the method        according to any of aspects 26 to 29, wherein said subject has        received prior anti cancer therapy with an immune checkpoint        inhibitor.    -   33. The composition for use according to aspect 25 or the method        according to any of aspects 26 or 29 further comprising        administering an anti cancer therapy with an immune checkpoint        inhibitor.    -   34. The composition for use or method according to aspect 33,        wherein the immune checkpoint inhibitor is administered before,        after or at the same time as the bacterial formulation.    -   35. The composition for use or method according to aspect 33 or        34, wherein the immune checkpoint inhibitor is administered by        injection.    -   36. The composition for use or method according to any of        aspects 33 to 35, wherein the injection is an intravenous,        intramuscular, intratumoural or subcutaneous injection.    -   37. The composition for use or method according to any of        aspects 33 to 36 wherein the immune checkpoint inhibitor        inhibits PD-1, PDL-1 or CTLA-4 activity.    -   38. The composition for use or method according to aspect 37,        wherein the immune checkpoint inhibitor is an anti PD-1, PDL-1        or CTLA-4 antibody.    -   39. The composition for use method according to aspect 38,        wherein the anti PD-1. PDL-1 or CTLA4 antibody is selected from        nivolumab, pembrolizumab, cemiplimab, avelumab, durvalumab,        atezolizumab, Spartalizumab, Camrelizumab, Sintilimab,        Tislelizumab, Pidilizumab, Toripalimab, Ipilimumab or        Tremelimumab.    -   40. The composition for use or method according to any of        aspects 33 to 37, wherein the immune checkpoint inhibitor is an        interfering nucleic acid molecule, a small molecule or        PROteolysis TArgeting Chimera (PROTAC) or other immune        checkpoint inhibitor.    -   41. The composition for use or method according to aspect 40,        wherein the interfering nucleic acid molecule is an siRNA        molecule, an shRNA molecule or an antisense RNA molecule or a        small molecule or peptide.    -   42. The composition for use according to aspect 25 or 30 to 41,        or the method according to any of aspects 26 to 41, further        comprising surgical, radiation, and/or chemotherapeutic cancer        intervention or administration of a second anti cancer        therapeutic.    -   43. The composition for according to aspect 25 or 30 to 42 or        method according to any of aspects 26 to 42, further comprising        administering to the subject an antibiotic.    -   44. The composition for use according to aspect 25 or 30 to 43        or method according to any of aspects 26 to 43, wherein the        subject is identified as at risk of developing a cancer.    -   45. A kit comprising a composition according to any of aspects 1        to 17, and optionally an anti cancer treatment that includes an        immune checkpoint inhibitor.    -   46. A food product or a vaccine adjuvant comprising the        composition of any of aspects 1 to 17.    -   47. A method for treating faecal transplant prior to        administration to a subject comprising supplementing the faecal        transplant with isolated bacteria selected from at least two        species wherein the bacteria from the first species comprise a        16S rDNA sequence having at least 98.7% sequence identity with a        nucleic acid sequence according to SEQ ID NO: 1, and the        bacteria from the second species comprise a 16S rDNA sequence        having at least 98.7% sequence identity with a nucleic acid        sequence according to SEQ ID NO: 2.    -   48. A use of a composition of any of aspects 1 to 17 or a        pharmaceutical composition of aspect 18, in increasing efficacy        of an anti cancer treatment with an immune checkpoint inhibitor.    -   49. A use of a composition of any of aspects 1 to 17 or a        pharmaceutical composition of aspect 18, in enhancing immune        checkpoint blockade.    -   50. A method for enhancing immune checkpoint blockade comprising        administering a composition of any of aspects 1 to 17 or a        pharmaceutical composition of aspect 18.    -   51. A composition comprising a bacterium selected from one or        more bacteria selected from Table 1.    -   52. A method for treating or preventing cancer comprising        modulating the level of one or more bacteria selected from those        of Table 1 in a subject.

The invention is also further described in the following additionalaspects.

-   -   1. A method for identifying a subject that will respond to        therapy with an immune checkpoint inhibitor comprising        determining the abundance of bacteria from at least 9 different        species in a biological sample from said subject that comprises        gut flora wherein said bacteria comprise a 16S rDNA sequence        selected from SEQ ID NOs: 1 to 15 or a sequence having at least        98.7% sequence identity with a nucleic acid sequence selected        from SEQ ID NOs: 1 to 15 wherein said abundance is indicative of        a response of a subject to therapy with an immune checkpoint        inhibitor.    -   2. The method for identifying a subject that will respond to        therapy with an immune checkpoint inhibitor according to aspect        1, the method comprising:        -   a) determining the abundance of the bacteria in a biological            sample obtained from the subject and        -   b) comparing the abundance to a reference level from cancer            patients that do not respond to therapy with an immune            checkpoint inhibitor or cancer patients that respond to            therapy with an immune checkpoint inhibitor;        -   wherein if the reference level is from patients that do not            respond to therapy with an immune checkpoint inhibitor, then            an increase in the abundance of each of the bacteria            compared to the reference level, is indicative that the            subject will respond to therapy with an immune checkpoint            inhibitor or        -   wherein if the reference level is from patients that do            respond to therapy with an immune checkpoint inhibitor, then            the same or substantially the same or an increase in            abundance of each of the bacteria, is indicative that the            subject will respond to therapy with an immune checkpoint            inhibitor.    -   3. The method for identifying a subject that will respond to        therapy with an immune checkpoint inhibitor according to aspect        1, the method comprising:        -   a) determining the abundance of the bacteria in a biological            sample obtained from the subject;        -   b) comparing the abundance to a reference level from cancer            patients and        -   c) applying random forest analysis.    -   4. The method according to a preceding aspect, wherein the        bacterial species comprise a 16S rDNA sequence selected from SEQ        ID NO: 1 or 2 or a 16S rDNA sequence having at least 98.7%        sequence identity thereto.    -   5. The method according to a preceding aspect, wherein the        method comprises determining the abundance of bacteria from 10,        11, 12, 13, 14 or 15 species wherein said bacteria comprise a        16S rDNA sequence selected from SEQ ID NOs: 1 to 15 or a        sequence having at least 98.7% sequence identity with a nucleic        acid sequence selected from SEQ ID NOs: 1 to 15.    -   6. The method according to a preceding aspect wherein said        subject is a cancer patient.    -   7. The method according to aspect 6, wherein the cancer is        selected from melanoma, bone cancer, pancreatic cancer, cancer        of the head or neck, cutaneous or intraocular malignant        melanoma, uterine cancer, ovarian cancer, rectal cancer, cancer        of the anal region, stomach cancer, testicular cancer, breast        cancer, brain cancer, carcinoma of the fallopian tubes,        carcinoma of the endometrium, carcinoma of the cervix, carcinoma        of the vagina, carcinoma of the vulva, cancer of the esophagus,        cancer of the small intestine, cancer of the endocrine system,        cancer of the thyroid gland, cancer of the parathyroid gland,        cancer of the adrenal gland, kidney cancer, sarcoma of soft        tissue, cancer of the urethra, cancer of the bladder, renal        cancer, lung cancer, non-small cell lung cancer, thymoma,        urothelial carcinoma leukemia, prostate cancer, mesothelioma,        adrenocortical carcinoma, lymphomas, such as such as Hodgkin's        disease, non-Hodgkin's, gastric cancer, and multiple myelomas.    -   8. The method according to aspect 7, wherein the melanoma is        selected from Harding-Passey melanoma, juvenile melanoma,        lentigo maligna melanoma, malignant melanoma, acral-lentiginous        melanoma, amelanotic melanoma, benign juvenile melanoma,        Cloudman's melanoma, S91 melanoma, nodular melanoma, subungual        melanoma, Cutaneous melanoma, uveal/intraocular melanoma and        superficial spreading melanoma.    -   9. The method according to a preceding aspect, further        comprising the step of identifying a subject in need of        treatment with the immune checkpoint inhibitor.    -   10. The method according to a preceding aspect, further        comprising administering an immune checkpoint inhibitor to said        subject.    -   11. The method according to a preceding aspect wherein the        immune checkpoint inhibitor inhibits PD-1, PD-L1 or CTLA-4        activity.    -   12. The method according to aspect 11, wherein the immune        checkpoint inhibitor is an anti PD-1, PDL-1 or CTLA-4 antibody.    -   13. The method according to aspect 12, wherein the anti PD-1,        PDL-1 or CTLA-4 antibody is selected from nivolumab,        pembrolizumab, cemiplimab, avelumab, durvalumab, atezolizumab,        Spartalizumab, Camrelizumab, Sintilimab, Tislelizumab,        Pidilizumab, Toripalimab, Ipilimumab or Tremelimumab.    -   14. The method according to any of aspects 1 to 11, wherein the        immune checkpoint inhibitor is an interfering nucleic acid        molecule, a small molecule or a PROteolysis TArgeting Chimera        (PROTAC) or other immune checkpoint inhibitor.    -   15. The method according to aspect 14, wherein the interfering        nucleic acid molecule is an siRNA molecule, an shRNA molecule or        an antisense RNA molecule or a small molecule or peptide.    -   18. The method according to a preceding aspect, wherein the        abundance is the abundance of the bacteria in the sample as a        proportion of the total microbiota in the sample.    -   17. The method according to a preceding aspect, further        comprising the step of obtaining a biological sample that        comprises gut flora from said subject.    -   18. The method according to a preceding aspect, wherein the        sample is a faecal sample.    -   19. Use of bacteria selected from at least 9 different bacterial        species wherein said bacteria comprise a 18S rDNA sequence        selected from SEQ ID NOs: 1 to 15 or a sequence having at least        98.7% sequence identity with a nucleic acid sequence selected        from SEQ ID NOs: 1 to 15 in identifying a patient that will        respond to therapy with an immune checkpoint inhibitor.    -   20. A kit comprising        -   a sealable container configured to receive a biological            sample;        -   polynucleotide primers for amplifying a 18S rDNA            polynucleotide sequence from at least 9 different bacterial            species wherein said bacteria comprise a 18S rDNA sequence            selected from SEQ ID NOs: 1 to 15 or a sequence having at            least 98.7% sequence identity with a nucleic acid sequence            selected from SEQ ID NOs: 1 to 15;        -   a detecting reagent to detect the amplified 16S rDNA            sequence; and instructions for use.    -   21. A method for identifying a faecal donor comprising assessing        a faecal sample of a subject for the presence of bacteria from        at least 9 different bacterial species wherein said bacteria        comprise a 16S rDNA sequence selected from SEQ ID NOs: 1 to 15        or a sequence having at least 98.7% sequence identity with a        nucleic acid sequence selected from SEQ ID NOs: 1 to 15 and        identifying the faecal donor based on the presence and/or        abundance of the bacteria.    -   22. The use of bacteria from at least 9 different bacterial        species wherein said bacteria comprise a 16S rDNA sequence        selected from SEQ ID NOs: 1 to 15 or a sequence having at least        98.7% sequence identity with a nucleic acid sequence selected        from SEQ ID NOs: 1 to 15 in a method for identifying a donor for        FMT therapy.    -   23. A method for determining if a cancer patient needs a        bacterial compensation before administration of an immune        checkpoint inhibitor comprising assessing, in a faeces sample        from said patient, the presence or absence of bacteria from at        least 9 different bacterial species wherein said bacteria        comprise a 16S rDNA sequence selected from SEQ ID NOs: 1 to 15        or a sequence having at least 98.7% sequence identity with a        nucleic acid sequence selected from SEQ ID NOs: 1 to 15.    -   24. A method for predicting a response to an immune checkpoint        inhibitor therapy in a subject having cancer comprising        determining the abundance of bacteria from at least 9 different        species wherein said bacteria comprise a 16S rDNA sequence        selected from SEQ ID NOs: 1 to 15 or a sequence having at least        98.7% sequence identity with a nucleic acid sequence selected        from SEQ ID NOs: 1 to 15 in a biological sample from said        subject that comprises gut flora wherein said abundance is        indicative of a response or non-response of a subject to therapy        with an immune checkpoint inhibitor.    -   25. A method for predicting a response to an immune checkpoint        inhibitor therapy in a subject having cancer according to aspect        24, the method comprising:        -   a) determining the abundance of the bacteria a biological            sample obtained from the subject;        -   b) comparing the abundance to a reference level from            patients that do not respond to immune checkpoint inhibitor            therapy; or patients that respond to immune checkpoint            inhibitor therapy; wherein if the reference level is from            patients that do not respond to immune checkpoint inhibitor            therapy, then an increase in the abundance of each of the            bacteria compared to the reference level, is indicative that            the subject will respond to therapy with an immune            checkpoint inhibitor or        -   wherein if the reference level is from patients that do            respond to immune checkpoint inhibitor therapy, then the            same or substantially the same or an increase in abundance            of each of the bacteria, is indicative that the subject will            respond to therapy with an immune checkpoint inhibitor.    -   26. The method according to aspect 24, the method comprising:        -   a) determining the abundance of the bacteria a biological            sample obtained from the subject and;        -   b) comparing the abundance to a reference level from cancer            patients or healthy subjects and        -   c) applying random forest analysis.    -   27. The method according to any of aspects 24 to 26, the method        comprising the step of predicting a response.    -   28. The method according to any of aspects 24 to 27, where if        the subject is predicted to be a non-responder, an anti cancer        therapy is administered which is not an immune checkpoint        inhibitor.    -   29. The method according to any of aspects 24 to 28, where if        the subject is predicted to be a non-responder, a composition        comprising isolated bacteria from one or more species is        administered wherein the bacteria comprise a sequence selected        from SEQ ID 1 to 15 or a sequence having at least 98.7% sequence        identity with a nucleic acid sequence selected from SEQ ID NOs:        1 to 15.    -   30. A method according to aspect 29, where if the subject is        predicted to be a non-responder, a composition comprising        isolated bacteria selected from at least two species is        administered wherein the bacteria from the first species        comprise a 16S rDNA sequence having at least 98.7% sequence        identity with a nucleic acid sequence according to SEQ ID NO: 1,        and the bacteria from the second species comprise a 16S rDNA        sequence having at least 98.7% sequence identity with a nucleic        acid sequence according to SEQ ID NO: 2.    -   31. A method according to aspect 29 or 31, wherein the        composition further comprises isolated bacteria from at least 1,        2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 different species        wherein the bacteria comprise a 16S rDNA sequence selected from        a sequence having at least 98.7% sequence identity with a        nucleic acid sequence according to SEQ ID NO: 3 to 15.    -   32. The method according to any of aspects 24 to 27, where if        the subject is predicted to be a responder, an immune checkpoint        inhibitor therapy is administered.

Further aspects and embodiments of the invention will be apparent tothose skilled in the art given the present disclosure including thefollowing experimental exemplification.

Unless otherwise defined herein, scientific and technical terms used inconnection with the present disclosure shall have the meanings that arecommonly understood by those of ordinary skill in the art. While theforegoing disclosure provides a general description of the subjectmatter encompassed within the scope of the present invention, includingmethods, as well as the best mode thereof, of making and using thisinvention, the following examples are provided to further enable thoseskilled in the art to practice this invention and to provide a completewritten description thereof. However, those skilled in the art willappreciate that the specifics of these examples should not be read aslimiting on the invention, the scope of which should be apprehended fromthe claims and equivalents thereof appended to this disclosure. Variousfurther aspects and embodiments of the present invention will beapparent to those skilled in the art in view of the present disclosure.

All documents mentioned in this specification are incorporated herein byreference in their entirety, including any references to gene accessionnumbers and references to patent publications.

“and/or” where used herein is to be taken as specific disclosure of eachof the two specified features or components with or without the other.For example, “A and/or B” is to be taken as specific disclosure of eachof (i) A, (ii) B and (iii) A and B, just as if each is set outindividually herein. Unless context dictates otherwise, the descriptionsand definitions of the features set out above are not limited to anyparticular aspect or embodiment of the invention and apply equally toall aspects and embodiments which are described.

The invention is further described in the non-limiting examples.

Example 1 Identification of Gut Bacteria and Isolates Driving Responseto Immunotherapy

The inventors have analysed how the microbiome of melanoma patientsimpacts response to immune checkpoint inhibitor therapy in the MELRESISTstudy. This study was conducted at Cambridge University Hospitals andwas performed with the best standards in sample collection andprocessing. The study involved 69 patients many of which hadlongitudinal faecal sampling. The inventors analysed the relativeabundance of gut bacteria in the baseline MELRESIST faecal samples byperforming shotgun metagenomic sequencing. The metagenomic sequencingwas analysed using a comprehensive and highly curated reference genomedatabase primarily built on reference-quality genomes from culturedisolates. This reference-based metagenomic analysis gives highlysensitive and accurate identification of bacteria (Forster et al NatBiotechnol. 2019; 37: 188). To support this analysis, the inventorsre-analysed three additional shotgun metagenomic datasets from melanomapatients about to receive immune checkpoint inhibitor therapy using thesame analysis platform.

The microbiome was examined by machine teaming approaches to select thespecific bacterial species most predictive of response to immunecheckpoint inhibitor therapy. For the first time in the field, aconsistent microbiome signature associated with and highly predictive ofresponse across multiple studies was identified. The size and quality ofthe MELRESIST dataset, the comprehensive and accurate identification ofbacteria by reference-based metagenomic analysis and machine learninganalysis all contributed to the discovery of this cross-study microbiomesignature. The signature also further validates the central importanceof the gut microbiome as a primary driver of immune checkpoint inhibitorresponse. This provides the basis for both a predictive biomarker andLive Bacterial Therapeutic co-therapy to increase the proportion ofpatients responding to checkpoint inhibitors. Using feature reductionsteps, this microbiome signature was reduced to small consortia ofbacteria comprising species more abundant in patients that response toimmunotherapy. These smaller consortia are still predictive of responseacross studies, so can act as a biomarker. In addition, these consortiacan form a live bacterial therapeutic for the co-administration withimmune checkpoint inhibitors in the treatment of cancer.

This analysis enabled the identification of strains isolatesrepresenting thirteen species in the consortia. Dendritic cellsstimulated with these strains, individually or as consortia of up tonine, potently activated Cytotoxic T Lymphocytes. Two consortia of ninewere also tested in a syngeneic mouse model of cancer and both consortiademonstrated tumour growth inhibition. These results validate thebacteria as drivers of anti-tumour response.

1.1 Discovery Based on MELRESIST Clinical Study

MELRESIST is a study performed at Cambridge University Hospitals inwhich 69 advanced melanoma patients gave a faecal sample prior to and/orfollowing treatment with anti-PD1 based immunotherapy. Complete clinicalmetadata, including response to therapy, antibiotic use and toxicities,was also recorded. A rigorous sample collection protocol was used toensure the highest possible standards. The DNA was extracted in a singlebatch at Microbiotica, and shotgun metagenomics performed. Shotgunmetagnomics sequencing is well known in the art and for exampledescribed in Quince, C. et al, Shotgun metagenomics, from sampling toanalysis. Nat Biotechnol 35, 833-844 (2017).

Reference-based metagenomics was used to analysis the sequences of thebaseline stool samples to give more sensitive and specificidentification of bacteria. The accuracy is further improved by abioinformatic tool to mask mobile elements thereby reducing spurioussignals caused by horizontal gene transfer. Suitable methods are alsodescribed in WO2020065347 incorporated by reference. Additionalclassification filtering removes mis-assigned reads caused bycontamination and gene duplication. The platform can accurately classifyover 95% of the metagenomic reads leading to a precise mapping of theabundance of almost every bacterium in the sample.

To support and validate the analysis, three additional datasets frommelanoma patients about to undergo immune checkpoint inhibitor therapywere reanalysed using the Microbiotica high-precision platform. Thesewere:

-   -   Frankel Neoplasia (2017) 19:848, Advanced melanoma, 39 patients    -   Gopalakrishnan et al and Wargo Science (2018) 359:97, Metastatic        melanoma, 25 patients (referenced as Wargo in figures)    -   Matson et al and Gajewski Science (2018) 359:104, Metastatic        melanoma, 39 patients (referenced as Gajewski in figures)

1.2 Bioinformatic Analysis to Derive Microbiome-Signatures Predictive ofResponse to Immunotherapy

The baseline samples from MELRESIST were used to define a signature ofresponse by linking the relative abundance of each bacteria in a sampleto the clinical outcome data. In the primary analysis stable disease,partial response and complete response at 6 months were all determinedto be a response and progressive disease was considered non-response.Machine learning approaches, including Random Forest models, were usedto select species providing the most power as part of a signature topredict response.

The random forest classifier is an algorithm based on the results ofmany decision trees. In a single decision tree, features are selectediteratively that best separate samples into responder and non-respondercategories, until all features are utilized. In the case of prevalencedata, these features could be presence or absence of a given species,where presence of a single species might be preferentially associatedwith responder samples, or vice versa. Alternatively, relative abundanceof a given species might be predictive of response, in which it could beeither more or less abundant in responder samples. Since a singledecision tree typically overfits data and does not produce robustresults, random forests are often used instead. A random forestclassifier is based on many different decision trees, where each treeonly uses a subset of the available data, for example randomly leavingout 20% of the observed species for each tree. In some cases, a subsetof the samples is used for training the random forest. The random forestclassifier thus learns which signals are strongest across all possiblefeatures and samples. For all random forest models, out-of-bag error wasused to prevent overoptimistic performance and improve generalizability.

The inventors expanded the analysis by including the additional melanomadatasets to identify the bacteria linked to response across multiplestudies. First, the data from the different studies was standardised,for example the response criteria was changed to be consistent with theMELRESIST study where necessary. A signature was then generated usingthe machine learning process on the combined dataset of all fourmelanoma datasets. The ability of this signature to function as abiomarker was then tested on the combined dataset, and it predictedwhether a patient would respond to therapy with an accuracy of 91% (FIG.1A). The Receiver Operating Characteristic (ROC) curve of this analysisgave an area under the curve (AUC) of 0.98 (FIG. 1C) thereby confirminghow highly predictive this signature is. Importantly, the signature was83-100% accurate when tested against the studies individually (FIG. 1B),and the ROC curves gave AUCs from 0.96 to 1 (FIG. 1D). This is the firstdemonstration of a microbiome based predictive biomarker that accuratelypredicts response across studies.

To progress the signature as a biomarker and select bacteria forinclusion in a Live Bacterial Therapeutic, the inventors identified thebacteria most robustly associated with response. The species that wereconsistently increased in abundance in responding patients from three orall four studies were selected to be advanced. Subsequently, a filteringstep was applied to choose the bacteria with the cleanest signal byexcluding species where the metagenomic reads did not broadly and evenlycover the genome.

The entire analysis was repeated from the start but excluding patientswith stable disease, where possible, to focus on bacteria linked to abetter clinical response. This reanalysis overlapped considerably withthe first thereby validating it and was used to refine the final list ofspecies. These analyses produced a list of 15 bacterial species,consortium 1, all increased in abundance in melanoma patients thatsubsequently responded to immune checkpoint inhibitor therapy acrossmultiple studies (see Table 1 and 3). The robustness of this reducedsignature was demonstrated by repeating the test as a biomarker in thecombined dataset, and it predicted whether a patient would respond totherapy with an accuracy of 77% (FIG. 2A). The Receiver OperatingCharacteristic (ROC) curve of this analysis gave an area under the curve(AUC) of 0.8 (FIG. 2C) thereby confirming how highly predictive thissignature is. Importantly, the signature was 67-84% accurate when testedagainst the studies individually (FIG. 2B), and the ROC gave AUCs from0.73 to 0.88 (FIG. 2D). Six additional consortia 2, 3, 4, 5, 6 and 10composed of 9 or 12 species (Table 3) from the 15 were also tested asbiomarkers, and had good predictivity of response both in the combineddataset and the individual studies (FIGS. 3-7 and 17).

Thus, the results show that the bacteria identified can be used aspredictive biomarker for response to anti-PD1 therapy in melanomapatients and also as a bacterial co-therapy to increase the proportionof melanoma patients responding to checkpoint inhibitors.

To understand if the bacteria could have utility in other cancerindications where checkpoint inhibitors are used, the inventors analysedthe predictive value of the full signature in a Non-Small Cell LungCancer (NSCLC) patient cohort (Routy et al 2018 Science 359:91-97). Thestudy sampled patients stool prior to anti-PD1 based therapy, andsubjected it to shotgun metagenomic sequencing. This was reanalysedusing the Microbiotica high-precision platform. The fifteen species inconsortium 1 were predictive of whether NSCLC patients would respond toanti-PD1 therapy (ROC AUC=0.722; FIG. 8). Therefore, the bacteriadescribed herein and discovered in melanoma patients are also linked toresponse in NSCLC. This shows that the bacteria described herein can beused as predictive biomarkers in another cancer indication. Moreover,this also suggests that the bacteria described herein can be used as abacterial co-therapy in other cancer indications.

1.3 Selection of Bacterial Isolates

The reference-based metagenomic analysis using genomes from culturedisolates enables the identified bacteria to be linked back to isolatesof the specific strains and/or closely related strains in the associatedculture collection. All available strains representing the species intable 1 underwent in silico characterisation to select for strains witha desirable developability and safety profile. The primary selectioncriteria consisted of anti-microbial resistance, bacteriophageproduction, and sporulation. Strains with a good profile were selectedfor further testing. These were expanded, cell banks generated, andgrowth characterised to enable testing in in vitro assays and in vivomodels. In addition, each strain has undergone full developability andsafety testing by laboratory testing and in silico analysis. For eachgenome assembly, 16S rDNA regions were identified in two ways. Firstly,using barmap (https://github.com/tseemann/barmap), and secondly byextracting, in silico, sequences of the desired length (between 1200 and1800 bp) by searching for DNA matches to the 7F(5′-AGAGTTTGATYMTGGCTCAG-3) (SEQ ID NO. 30) 1510R(5′-ACGGYTACCTTGTTACGACTT-3) (SEQ ID NO. 31) universal 16S primers.Where multiple overlapping 16S sequences were extracted from anassembly, the longest was retained.

1.4 Host Interaction

The lead bacteria have been selected based on a strong association withclinical response across multiple studies, and, therefore, areconsidered suitable candidates for inclusion in a Live BacterialTherapeutic. To understand the mechanism of action, the bacteria havebeen profiled individually, as a complete consortium and assub-consortia in several in vitro assays with human cells. Cytotoxic TLymphocytes (CTLs) are a significant effector cell in anti-tumour immuneresponses by directly lysing tumour cells via granzyme B and perforinrelease and production of cytokines such as IFNγ. CTLs can expressco-stimulatory and co-inhibitory receptors. Immune checkpoint inhibitortherapies block the suppression of CTL activity by blocking theinteraction between co-inhibitory receptor (eg PD-1) and their ligands(eg PD-L1). The later can be expressed by tumour cells as a mechanism toescape immune-mediated depletion, which is reversed by checkpointinhibitor therapy. CTLs are activated and educated by dendritic cells,which are a sentinel innate immune cells that have many receptors tosense and respond to bacteria. Therefore, the bacteria identified(individually or as consortia) were tested for an ability to stimulatedendritic cells (DCs), and then if these DCs activate CTLs.

Bacterial strains representing thirteen of the fifteen species wereidentified and grown in bacterial media. These were washed and added inco-cultured with human monocyte-derived DCs in anaerobic conditions.Antibiotics were then added and the DCs cultured in an aerobicenvironment. The activation of DCs was measured by upregulation of thematuration markers CD88 (a co-stimulatory ligand) and CD83. Eleven ofthe thirteen species robustly induced expression of both markers withGordonibacter urolithinfaciens and Alistipes indictincus being pooractivators of DC maturation (FIGS. 9A and 9B). Indeed, many induced asimilar level of CD86 and CD83 express as the positive controls,lipopolysaccharide (LPS), Poly I:C and Salmonella typhimurium, all ofwhich are known to be very potent activators of DCs. Two consortia ofnine species (Consortia 5 and 6), as well as sub-consortia of consortium6 containing six, three and two species all also triggered DC maturationas measured by CD86 and CD83 upregulation (FIG. 9B-9E). The bacteriaalso triggered cytokine release from the DCs. IL-12 is a very importantcytokine for the priming of a CTL response, and IL-10 is associated withsuppression of T cell response. Therefore, the ratio of IL-12 to IL-10was used to measure whether the DCs could be a strong inducer of apositive CTL response. The nine of the ten species tested and Consortia5 and 6 triggered higher levels of IL-12 than IL-10 even when comparedto strong inflammatory stimuli like LPS and Poly I:C (FIG. 9G). The datafrom Gordonibacter urolithinfaciens is not shown because the levels ofcytokines released was too low to make a ratio meaningful. These dataindicate that the bacteria identified as being associated with responseto immune checkpoint inhibitor therapy are by enlarge potent activatorsof DC maturation, and release cytokines that could direct an enhanced Tcell response.

To understand how effective these DCs were at stimulating CTLs, themature DCs were co-cultured with allogenic CD8 expressing T cells (CTLs)for 6 days. CTLs activation was quantified by upregulation of GranzymeB, perforin and IFNγ. Thirteen of the bacterial species were tested, andall were shown to induce DCs that can potentially activate CTLs (FIG.10). The level of activation was comparable to or better than the stronginflammatory stimuli LPS, Poly I:C and Salmonella typhimurium.Interesting, even Gordonibacter urolithinfaciens and Alistipesindictincus were shown to lead to robust CTLs activation despite beingpoor stimulators of CD86 and CD83 expression by DCs. The consortiatested (5, 6, 7, 8 and 9) also all induced strong CTL activation (FIGS.11 and 12). These data demonstrate that the bacteria identified as beingassociated with response to immune checkpoint inhibitor therapy arepotent activators of a CTL response via stimulation of DCs. This is trueof the individual species and of consortia of two to nine species. Thisinduction of CTL activation could be a key mechanism by which the raisedabundance of these bacteria leads to enhanced anti-tumour immunity inthe presence of anti-PD1. It could also indicate that a therapeuticcomposition comprising these bacteria could enhance a vaccine responseand/or anti-viral immunity.

The bacteria lead to potent CTL activation, so their ability to killtumour cells was tested next. In this assay, the CTLs activated bybacteria-stimulated DCs were co-cultured with the tumour cell lineSKOV-3 cells. All ten of the species tested led to potent cytolysis ofthe tumour cells by CTLs as measured by a decrease in electricimpedance. The level of tumour cell killing compared favourably to theother known strong innate stimuli. The consortia tested (5, 6, 7, 8 and9) also led to high levels of tumour cell killing (FIGS. 13 and 14).These data demonstrate that the bacteria identified as being associatedwith response to immune checkpoint inhibitor therapy are potentactivators of an immune-mediated tumour cell killing. This is true ofthe individual species tested and of consortia of two to nine species.

In total, the above data show that the bacterial species identified asbeing associated anti-PD-1 response are able to stimulate DCs to triggerCTLs activation and tumour cell killing. This mechanism is likely toexplain, at least in part, why these bacteria are associated withresponse to anti-PD-1 based therapy in melanoma. This mechanism isassociated with immune checkpoint inhibitor efficacy in multiple tumoursindicating that the bacteria described herein can be used as a bacterialco-therapy in other cancer indications. Indeed, the bacteria describedherein are likely to be an effective co-therapy with any immunotherapythat enhances CTL response for example adoptive T cell transfer therapyand CAR-T cell therapy. Interestingly, two of the strains tested(Gordonibacter urolithinfaciens and Alistipes indictincus) did notinduce classical markers of DC activation (CD86 and CD83), but the DCsstill induced CTL activation.

The type 1 interferons (IFNs), IFNα and IFNβ, are potent inducers of CTLimmunity and can have direct anti-tumour effects. Plasmacytold dendriticcells are capable of producing very high levels of IFNα and IFNβ. Totest if the isolated bacteria associated with anti-PD-1 response inducedIFNα release, plasmacytold dendritic cells were stimulated with strainsrepresenting nine of the species. Plasmacytoid dendritic cells did nottolerate anaerobic conditions, so heat-killed bacteria were used in anaerobic environment. Seven of the nine strain induced IFNα release fromplasmacytoid DCs (FIG. 15). This could be another potential mechanism bywhich these bacteria enhance anti-tumour immune responses. Interesting atonic type 1 interferon signal from the microbiome has been implicatedin enhancing anti-viral responses in the lung (Bradley et al 2019 CellReports 28:245-256). Therefore, the species identified may alsopotential drive an anti-viral response and/or anti-viral vaccineefficacy.

In addition, to the above mechanistic assays two selected consortia weretested for efficacy in a syngeneic model of cancer. SPF mice weretreated with antibiotics before engrafting the microbiome of a melanomapatient one day prior to implanting MCA205 tumour cells. Dosingconsortium 5 or 6 by oral gavage induce tumour growth inhibition (FIG.16) although not to the same degree as the positive control (anti-PD1).This shows the anti-tumour potential of these consortia, and validatesthe selection of these species by association with improved clinicaloutcome. MCA-205 is a fibrosarcoma cell lines, which furtherdemonstrates that the bacteria described herein have potential in cancerindications beyond melanoma. Together the data presented here shows wehave identified bacterial species predictive of response to checkpointinhibitor therapy in multiple melanoma studies and in NSCLC. Thesespecies are able to stimulate DCs leading to the activation of CTLs andtumour cell killing. Two consortia of these species are furthervalidated in an in vivo cancer model.

TABLE 2 Sequences SEQ ID 16S rDNA Sequence SEQ IDAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAAGT No. 1CGAACGGAGTTATGCAGAGGAAGTTTTCGGATGGAATCGGCGTAACTTAGTGGCGGACGGGTGAGTAACGCGTGGGAAACCTGCCCTGTACCGGGGGATAACACTTAGAAATAGGTGCTAATACCGCATAAGCGCACAGCTTCACATGAGGCAGTGTGAAAAACTCCGGTGGTACAGGATGGTCCCGCGTCTGATTAGCCAGTTGGCAGGGTAACGGCCTACCAAAGCGACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGTGAGTGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGGGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGGCATGACAAGCCAGATGTGAAAACCCAGGGCTCAACCCTGGGACTGCATTTGGAACTGCCAGGCTGGAGTGCAGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACTGTAACTGACGTTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCGGTAAACGATGATTGCTAGGTGTAGGTGGGTATGGACCCATCGGTGCCGCAGCTAACGCAATAAGCAATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCAATGACGTGTCCGTAACGGGGCATTCTCTTCGGAGCATTGGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATCCTTAGTAGCCAGCAGGTAGAGCTGGGCACTCTAGGGAGACTGCCGGGGATAACCCGGAGGAAGGCGGGGATGACGTCAAATCATCATGCCCCTTATGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGTGATGTTGAGCAAATCCCAGAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGAAGCTGGAATCGCTAGTAATCGCGAATCAGCATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGCCTGTGACCTAACCGCAAGGGAGGAGCAGTCGAAGGCAGGTCTAATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTTTAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 2GTCGAACGGAGTTATTTTGGAAATCTCTTCGGGGATGGAATTCATAACTTAGTGGCGGACGGGTGAGTAACGCGTGAGCAATCTGCCCTTAGGTGGGGGATAACAGCCGGAAACGGCTGCTAATACCGCATAACACATTGAAGCCGCATGGTTTTGATGTCAAAGATTTATTGCCTTTGGATGAGCTCGCGTCTGATTAGCTGGTTGGCGGGGTAACGGCCCACCAAGGCGACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCAACGCCGCGTGATTGAAGAAGGCCTTCGGGTTGTAAAGATCTTTAATTGGGGACGAATTTTGACGGTACCCAAAGAATAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGCGAGTAGGCGGGCTGGCAAGTTGGGAGTGAAATCCCGGGGCTTAACCCCGGAACTGCTTTCAAAACTGCTGGTOTTGAGTGATGGAGAGGCAGGCGGAATTCCGTGTGTAGCGGTGAAATGCGTAGATATACGGAGGAACACCAGTGGCGAAGGCGGCCTGCTGGACATTAACTGACGCTGAGGAGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGGATACTAGGTGTGGGAGGTATTGACCCCTTCCGTGCCGGAGTTAACACAATAAGTATCCCACCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTCTTGACATCCCTCTGACCGCCCTAGAGATAGGGTTTCCCTTCGGGGCAGAGGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTACGGTTAGTTGATACGAAAGATCACTCTAGCCGGACTGCCGTTGACAAAACGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTACTACAATGGCAGTCATACAGAGGGAAGCAAAACAGTGATGTGGAGCAAATCCCTAAAAGCTGTCCCAGTTCAGATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGAATTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGAGAGCCGGTAATACCCGAAGTCCGTAGCCTAACCGCAAGGAGGGCGCGGCCGAAGGTAGGACTGGTAATTAGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTTTAAGAGTTTGATCCTGGCTCAGGACGAACGCTGGCGGCGTGCCTAACACATGCAAG No. 3TCGAACGAAGCTTGATTTCTGATTTTTTCGGAATGACGAATGATATGACTGAGTGGCGGACGGGTGAGTAACGCGTGAGCAACCTGCCCTTOGGAACGGGATAGTGTCTGGAAACGGACAGTAATACCGTATAATATATATTGATCGCATGGTTGATATATCAAAACTGAGGTGCCGAAGGATGGGCTCGCGTCTGATTAGATAGTTGGTGGGGTAACGGCCTACCAAGTCGACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAAGGAAGACGGTTTTCGGATTGTAAACTTCTGTTCTTAGTGAAGAATAATGACGGTAGCTAAGGAGCAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAATTACTGGGTGTAAAGGGAGCGTAGGCGGGATGCCAAGTCAGCTGTGAAAACTATGGGCTTAACTTGTAGACTGCAGTTGAAACTGGTATTCTTGAGTGAAGTAGAGGTTGGCGGAATTCCGAGTGTAGOGGTGAAATGCGTAGATATTCGGAGGAACACCGGTGGCGAAGGCGGCCAACTGGGCTTTAACTGACGCTGAGGCTCGAAAGTGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACACTGTAAACGATGATAACTAGGTGTGGGGGGTCTGACCCCTTCCGTGCCGCAGCTAACGCAATAAGTTATCCACCTGGGGAGTACGACCGCAAGGTTGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCAGTGGATTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGCACTTGACATCCGACTAACGAAGTAGAGATACATTAGGTGCCCTTCGGGGAAAGTCGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTOCCGCAACGAGCGCAACCCCTGCCATTAGTTGCTACGCAAGAGCACTCTAATGGGACCGCTACCGACAAGGTGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGTGCTGGGCTACACACGTAATACAATGGCCATCAACAAAGAGAAGCAATACCGCGAGGTGGAGCAAAACTATAAAAATGGTCTCAGTTCGGACTGCAGGCTGCAACCCGCCTGCACGAAGTTGGAATTGCTAGTAATCGTGGATCAGCATGCCACGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTTGGTAACACCCGAAGTCAGTAGTCTAACCGCAAGGAGGACGCTGCCGAAGGTGGGATTGACGACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCAGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGGCAGGCTTAACACATGCAA No. 4GTCGAGGGGCAGCATAATGGTAGCAATACTATTGATGGCGACCGGCGGACGGGTGCGTAACGCGTATGCAACCTACCCTTTACAGGGGGATAACACTGAGAAATCGGTACTAATACCCCATAATATTCTGGGAGGCATCTTTOGGAGTTGAAAGCTTTGGTGGTAAAGGATGGGCATGCGTTGTATTAGCTAGTTGGTAAGGTAACGGCTTACCAAGGCGACGATACATAGGGGGACTGAGAGGTTAACCCCCCACATTGGTACTGAGACACGGACCAAACTCCTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGACGGAAGTCTGAACCAGCCATGCCGCGTGCAGGAAGACGGCTCTATGAGTTGTAAACTGOTTTTGTACGAGGGTAAACGCAGATACGTGTATCTGCCTGAAAGTATCGTACGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCAAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGTAGGCGGTTTAGTAAGTCAGCGGTGAAATTTTGGTGOTTAACACCAAACGTGCCGTTGATACTGCTGGGCTAGAGAGTAGTTGCGGTAGGCGGAATGTATGGTGTAGCGGTGAAATGCTTAGAGATCATACAGAACACCGATTGCGAAGGCAGCTTACCAAACTATATCTGACGTTGAGGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCAGTAAACGATGATAGCTCGTTGTCGGCGATACACAGTCGGTGACTAAGAGAAATCGATAAGCTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCGGGCTTGAAAGTTACTGACGATTCTGGAAACAGGATTTCCCTTCGGGGCAGGAAACTAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAACGAGCGCAACCCCTACTGATAGTTGCCATCAGAGCGTTTGAGCGATCAAACAAGCTGGGCACTCTATCGGGACTGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGTAGGTACAGAGGGCAGCCACCCAGTGATGGGGAGCGAATCTCGAAAGCCTATCTCAGTTCGGATTGGAGGCTGAAACTCGCCTCCATGAAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGGAGTTGGGGGTGCCTGAAGTTCGTGACCGAAAGGAGCGACCTAGGGCAAAACCGATGACTGGGGCTAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ IDATGGAGAGTTTGATCCTGGCTCAGGATAAACGCTAGCGGCAGGCCTAACACATGCAA No. 5GTCGAGGGGCAGCGGGTGGAGTATTTCGGTACTCCTGCCGGCGACCGGCGCACGGGTGCGTAACGCGTATGCAACCTACCTTTAACAGGGGGATAATCCGAAGAAATTTGGTCTAATACCCCATAATATCATTTAAGGCATCTTAGATGGTTGAAAATTCCGATGGTTAGAGATGGGCATGCGTTGTATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCTACGATACATAGGGGGACTGAGAGGTTTTCCCCCCACACTGGTACTGAGACACGGACCAGACTCCTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGACGCAAGTCTGAACCAGCCATGCCGCGTGCAGGATGAAGGTGCTATGCATTGTAAACTGCTTTTGTACGAGGGTAAATGCAGGTACGTGTACCTGTTTGAAAGTATCGTACGAATAAGGGTCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGACCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGTAGGCGGATTAGTAAGTTAGAGGTGAAAGCTCGATGCTCAACATCGAAATTGCCTCTGATACTGTTAGTCTAGAGTATAGTTGCGGAAGGCGGAATGTGTGGTGTAGCGGTGAAATGCTTAGATATCACACAGAACACCGATTGCGAAGGCAGCTTTCCAAGCTATTACTGACGCTGATGCACGAAAGCGTGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGATAACTCGTTGCAGGCGATACACAGTCTGTGACTTAGCGAAAGCGTTAAGTTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCGGGCTTGAAAGTTAGCGACGGATCCTGAAAGGGGTCTTCTCTTCGGAGCGCGAAACTAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAACGAGCGCAACCCCTACTGTTAGTTACCAGCACGTCAAGGTGGGCACTCTAGCAGGACTGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGTCGGTACAGAGGGTCGCTACCCCGTGAGGGGATGCCAATCTCGAAAGCCGATCTCAGTTCGGATTGGAGGCTGAAACTCGCCTCCATGAAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGGAGTTGGGGGTGCCTGAAGTACGTGACCGCAAGGAGCGTCCTAGGGCAAAACCGATGACTGGGGCTAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTT SEQ IDACGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 6GTCGAACGGTTAAGGCGCCTTCGGGCGCGAATAGAGTGGCGAACGGGTGAGTAACACGTGACCAACCTGCCCCCCTCCCCGGGATAACGCGAGGAAACCCGCGCTAATACCGGATACTCCGCCCCTCCCGCATGGGAGGGGCGGGAAAGCCCCGACGGAGGGGGATGGGGTCGCGGCCCATTAGGTAGACGGCGGGGCAACGGCCCACCGTGCCTGCGATGGGTAGCCGGGTTGAGAGACCGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGCGCAATGGGGGGAACCCTGACGCAGCAACGCCGCGTGCGGGACGAAGGCCTTCGGGTTGTAAACCGCTTTCAGCAGGGAAGAAGTTGACGGTACCTGCAGAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCGAGCGTTATCCGGATTCATTGGGCGTAAAGCGCGCGTAGGCGGCCCGTCAAGCGGAACCTCTAACCCGAGGGCTCAACCCCCGGCCGGGTTCCGAACTGGCAGGCTCGAGTTTGGTAGAGGAAGATGGAATTCCCGGTGTAGCGGTGGAATGCGCAGATATCGGGAAGAACACCGATGGCGAAGGCAGTCTTCTGGGCCATCAACTGACGCTGAGGCGCGAAAGCTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCCAGCCGTAAACGATGGGTGCTAGGTGTGGGGGGATCATCCCTCCGTGCCGCAGCCAACGCATTAAGCACCCCGCCTGGGGAGTACGGCCGCAAGGCTAAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGCGGAGCATGTGGCTTAATTCGAAGCAACGCGAAGAACCTTACCAGGGCTTGACATGCTGGTGAAGCCGGGGAAACCCGGTGGCCGAGAGGAGCCAGCGCAGGTGGTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGCCATATGTTGCCAGCATTCAGTTGGGGACTCATATGGGACTGCCGGCGTCAAGCCGGAGGAAGGTGGGGACGACGTCAAGTCATCATGCCCTTTATGCCCTGGGCTGCACACGTGCTACAATGGCCGGTACAACGGGCCGCGACCTGGCGACAGGAAGCGAATCCCTCAAAGCCGGCCCCAGTTCGGATCGGAGGCTGCAACCCGCCTCCGTGAAGTCGGAGTTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACCCGAGTCGTCTGCACCCGAAGCCGCCGGCCGAACCCGCAAGGGGCGGAGGCGTCGAAGGTGTGGAGGGTAAGGGGGGTGAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCATGCCTAATACATGCAAG No. 7TCGAACGAAGTOTTTAGGAAGCTTGCTTCCAAAGAGACTTAGTGGCGAACGGGTGAGTAACACGTAGGTAACCTGCCCATGTGCCCGGGATAACTGCTGGAAACGGTAGCTAAAACCGGATAGGTATGAGGGAGGCATCTTCCTCATATTAAAGCACCTTCGGGTGTGAACATGGATGGACCTGCGGCGCATTAGCTGGTTGGTGAGGTAACGGCCCACCAAGGCGATGATGCGTAGCCGACCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAAACTCCTACGGGAGGCAGCAGTAGGGAATTTTCGTCAATGGGGGGAACCCTGAACGAGCAATGCCGCGTGTGTGAAGAAGGTCTTCGGATCGTAAAGCACTGTTGTAAGTGAAGAATGCCATATAGAGGAAATGCTATGTGGGTGACGGTAGCTTACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATCATTGGGCGTAAAGGGTGCGTAGGTGGCACGATAAGTCTGAAGTAAAAGGCAACAGCTCAACTGTTGTATGCTTTGGAAACTGTCGAGCTAGAGTGCAGAAGAGGGCGATGGAATTCCATGTGTAGCGGTAAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGTCGCCTGGTCTGTAACTGACACTGATGCACGAAAGCGTGGGGAGCAAATAGGATTAGATACCCTAGTAGTCCACGCCGTAAACGATGAGAACTAAGTGTTGGAGAGATTCAGTGCTGCAGTTAACGCAATAAGTTCTCCGCCTGGGGAGTATGCACGCAAGTGTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGCCTTGACATGGATATAAATGTTCTAGAGATAGAAAGATAGCTATATATCACACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCTTCTGTTACCAGCATTAAGTTGGGGACTCAGGAGAGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGGCCTGGGCTACACACGTACTACAATGGCGCCTACAAAGAGCAGCGACACCGCGAGGTGGAGCGAATCTCATAAAGGGCGTCTCAGTTCGGATTGAAGTCTGCAACTCGACTTCATGAAGTCGGAATCGCTAGTAATCGCAGATCAGCATGCTGCGGTGAATACGTTCTCGGGCCTTGTACACACCGCCCGTCAAACCATGGGAGTTGGTAATACCCGAAGCCGGTGGCATAACCGCAAGGAGTGAGCCGTCGAAGGTAGGACCGATGACTGGGGTTAAGTCGTAACAAGGTATCCCTACGGGAACGTGGGGATGGATCACCTCCTTT SEQ IDTCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 8GTCGAGCGAAGCACTTAAGTGGATCTCTTCGGATTGAAACTTATTTGACTGAGCGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTAGAAATGGCTGCTAATACCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTCCGGTGGTATGAGATGGACCCGCGTCTGATTAGCTAGTTGGAGGGGTAACGGCCCACCAAGGCGACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGGGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGGAAGAGCAAGTCTGATGTGAAAGGCTGGGGCTTAACCCCAGGACTGCATTGGAAACTGTTTTTCTAGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGTTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGTGGCAAAGCCATTCGGTGCCGCAGCAAACGCAATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCTCTGACCGGCCCGTAACGGGGCCTTCCCTTCGGGGCAGAGGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTATCCTTAGTAGCCAGCAGGTAGAGCTGGGCACTCTAGGGAGACTGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGCGATGTTGAGCAAATCCCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCACGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCCAACCTTACAGGAGGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDCGAAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGACAGGCCTAACACATGCAAGT No. 9CGAGGGGCAGCGGAGAGGTAGCAATACCTTTGCCGGCGACCGGCGCACGGGTGAGTAACACGTATGCAATCCACCTGTAACAGGGGGATAACCCGGAGAAATCCGGACTAATACCCCATAATATGGGCGCTCCGCATGGAGAGTCCATTAAAGAGAGCAATTTTGGTTACAGACGAGCATGCGCTCCATTAGCCAGTTGGCGGGGTAACGGCCCACCAAAGCGACGATGGATAGGGGTTCTGAGAGGAAGGTCCCCCACATTGGAACTGAGACACGGTCCAAACTCCTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGTCGGCAGACTGAACCAGCCAAGTCGCGTGAGGGAAGACGGCCCTACGGGTTGTAAACCTCTTTTGTCGGAGAGTAAAGTACGCTACGTGTAGTGTATTGCAAGTATCCGAAGAAAAAGCATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATGCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGTAGGCGGCACGCCAAGTCAGCGGTGAAATTTCCGGGCTCAACCCGGACTGTGCCGTTGAAACTGGCGAGCTAGAGTGCACAAGAGGCAGGCGGAATGCGTGGTGTAGCGGTGAAATGCATAGATATCACGCAGAACCCCGATTGCGAAGGCAGCCTGCTAGGGTGCGACAGACGCTGAGGCACGAAAGCGTGGGTATCGAACAGGATTAGATACCCTGGTAGTCCACGCAGTAAACGATGAATACTAACTGTTTGCGATACAATGTAAGCGGTACAGCGAAAGCGTTAAGTATTCCACCTGGGGAGTACGCCGGCAACGGTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCGGGCTCAAACGCAGGGGGAATGCCGGTGAAAGTCGGCAGCTAGCAATAGTCACCTGCGAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGCTTAAGTGCCATAACGAGCGCAACCCCTATGGACAGTTACTAACGGGTGAAGCCGAGGACTCTGTCTAGACTGCCGGCGCAAGCCGCGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGCAGGTACAGAAGGCAGCCAGTCAGCAATGACGCGCGAATCCCGAAAACCTGTCTCAGTTCGGATTGGAGTCTGCAACCCGACTCCATGAAGCTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGAAGCCGGGAGTACCTGAAGCATGCAACCGCAAGGAGCGTACGAAGGTAATACCGGTAACTGGGGCTAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ IDATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGGCAGGCCTAACACATGCAA No. 10GTCGAGGGGCAGCGGGATTGAAGCTTGCTTCAATCGCCGGCGACCGGCGCACGGGTGCGTAACGCGTATGCAACCTACCCAGAACAGGGGGATAACACTGAGAAATTGGTACTAATATCCCATAACATCATAAGGGGCATCCCTTTTGGTTGAAAACTCCGGTGGTTCTGGATGGGCATGCGTTGTATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATACATAGGGGGACTGAGAGGTTAACCCCCCACATTGGTACTGAGACACGGACCAAACTCCTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGACGCAAGTCTGAACCAGCCATGCCGCGTGCAGGAAGACGGCTCTATGAGTTGTAAACTGCTTTTGTACTAGGGTAAACTCAGATACGTGTATCTGACTGAAAGTATAGTACGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATTCAAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGTAGGCGGTTTGATAAGTTAGAGGTGAAATACCGGTGCTTAACACCGGAACTGCCTCTAATACTGTTGAGCTAGAGAGTAGTTGCGGTAGGCGGAATGTATGGTGTAGCGGTGAAATGCTTAGAGATCATACAGAACACCGATTGCGAAGGCAGCTTACCAAACTATATCTGACGTTGAGGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCAGTAAACGATGATAACTCGCTGTCGGCGATACACAGTCGGTGGCTAAGCGAAAGCGATAAGTTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCGGGCTTGAAAGTTAGTGACGGATCTGGAAACAGGTOTTCCCTTCGGGGCGCGAAACTAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAACGAGCGCAACCCCTACCGTTAGTTGCCATCAGGTCAAGCTGGGCACTCTGACGGGACTGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACGTCCGGGGCCACACACGTGTTACAATGGTAGGTACAGAGGGCAGCTACCCAGCGATGGGATGCGAATCTCGAAAGCCTATCTCAGTTCGGATCGGAGGCTGAAACCCGCCTCCGTGAAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGAAGCTGGGGGTGCCTGAAGTTCGTGACCGCAAGGAGCGACCTAGGGCAAAACCGGTGACTGGGGCTAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ IDTCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 11GTCGAGCGAAGCACTTGCCATTGACTCTTCGGAAGATTTGGCATTTGACTGAGCGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGAATAACAGTTAGAAATGGCTGCTAATGCCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTGAGGTGGTATGAGATGGGCCCGCGTCTGATTAGGTAGTTGGCGGGGTAACGGCCCACCAAGCCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTGATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGGGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGGACGGGCAAGICTGATGTGAAAGCCCGGGGCTTAACCCCGGGACTGCATTGGAAACTGTCCATCTTGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGTTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGTTGCAAAGCAATCCGGTGCCGCAGCAAACGCAGTAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCTGCCTGACCGTTCCTTAACCGGAACTTTCCTTCGGGACAGGCAAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGTCCTTAGTAGCCAGCAGTCCGGCTGGGCACTCTAGGGAGACTGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGTGGTGACACTGAGCAAATCTCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCACGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCTAACCGCAAGGGAGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTTATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 12GTCGAACGAAGCATTTAAGACGGATTCTTTCGGGATGAAGACTTTTATGACTGAGTGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCACACAGGGGGATAGCAGTTGGAAACGGCTGATAATACCGCATAAGCGCACAGTACCGCATGGTACAGTGTGAAAAACTCCGGTGGTGTGAGATGGACCCGCGTCTGATTAGCTTGTTGGCAGGGTAACGGCCTACCAAGGCAACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTGATGCAGCGACGCCGCGTGAGTGAAGAAGTAATTCGTTATGTAAAGCTCTATCAGCAGGGAAGATAGTGACGGTACCTGACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGGTGGCATCACAAGTCAGAAGTGAAAGCCCGGGGCTCAACCCCGGGACTGCTTTTGAAACTGTGGAGCTGGAGTGCAGGAGAGGCAAGTGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTGCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGGCTCATAAGAGCTTCGGTGCCGCAGCAAACGCAATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCTCTTGACCGGTCAGTAATGTGACCTTTTCTTCGGAACAAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTATTCTTAGTAGCCAGCATTTAAGGTGGGCACTCTAGGAAGACTGCCAGGGATAACCTGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGTGAAGCGAGAGTGTGAGCTTAAGCAAATCACAAAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCGGAAATGCCCGAAGTCGGTGACCTAACGAAAGAAGGAGCCGCCGAAGGCAGGTCTGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTAAAGAGTTTGATCCTGGCTCAGGACGAACGCTGGCGGCACGCTTAACACATGCAAGT No. 13CGAACGGAGAATATCGAAGCTTGCTTTGATATTCTTAGTGGCGGACGGGTGAGTAACACGTGAGTAACCTGCCTCTGAGAGTGGGATAGCTTCTGGAAACGGATGGTAATACCGCATGAAATCATAGTATCGCATGGTACAATGATCAAAGATTTATCGCTCAGAGATGGACTCGCGTCTGATTAGCTAGTTGGTAAGGTAACGGCTTACCAAGGCGACGATCAGTAGCCGGACTGAGAGGTTGATCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGATGCCGCGTGGAGGAAGAAGGTTTTCGGATTGTAAACTCCTGTTGAAGAGGACGATAATGACGGTACTCTTTTAGAAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGAGCGAGCGTTGTCCGGAATTACTGGGTGTAAAGGGAGCGTAGGCGGGACGGCAAGTCAGATGTGAAAACTATGGGCTCAACCCATAGACTGCATTTGAAACTGTTGTTCTTGAGTGAGGTAGAGGTAAGCGGAATTCCTGGTGTAGCGGTGAAATGCGTAGAGATCAGGAGGAACATCGGTGGCGAAGGCGGCTTACTGGGCCTTTACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGATTACTAGGTGTGGGGGGACTGACCCCTTCCGTGCCGCAGTTAACACAATAAGTAATCCACCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTOTTGACATCGAGTGACGTACCTAGAGATAGGTATTTTCTTCGGAACACAAAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTACCATTAGTTGCTACGCAAGAGCACTCTAATGGGACTGCCGTTGACAAAACGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTACTACAATGGCAATATAACAGAGGGAAGCAATACAGCGATGTGGAGCAAATCCCCAAAAATTGTCCCAGTTCAGATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGAATTGCTAGTAATCGCAGATCAGCATGCTGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTCGGTAACACCCAAAGCCGGTCGTCTAACCTTCGGGAGGACGCCGTCTAAGGTGGGATTGATGACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATC ACCTCCTTTSEQ ID ATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAAGT No. 14CGAACGAAGCACTCTATTTGATTTTCTTCGGAAATGAAGATTTTGTGACTGAGTGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTGGAAACGACTGCTAATACCGCATAAGCGCACAGGATCGCATGGTCCGGTGTGAAAAACTCCGGTGGTATGAGATGGACCCGCGTCTGATTAGCCAGTTGGCAGGGTAACGGCCTACCAAAGCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGGGAAGAAGAATGACGGTACCTGACTAAGAAGCACCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGTGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGCAGGCGGTGCGGCAAGTCTGATGTGAAAGCCCGGGGCTCAACCCCGGTACTGCATTGGAAACTGTCGTACTAGAGTGTCGGAGGGGTAAGTGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGATAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGGAGCATTGCTCTTCGGTGCCGCAGCAAACGCAATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCGATGACAGAGTATGTAATGTACTTTCTCTTCGGAGCATCGGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGTTCTTAGTAGCCAGCGGTTCGGCCGGGCACTCTAGGGAGACTGCCAGGGATAACCTGGAGGAAGGCGGGGATGACGTCAAATCATCATGCCCCTTATGACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGCCGTGAGGCCGAGCAAATCTCAAAAATAACGTCTCAGTTCGGACTGTAGTCTGCAACCCGACTACACGAAGCTGGAATCGCTAGTAATCGCAGATCAGAATGCTGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGTCAGTGACCCAACCGCAAGGAGGGAGCTGCCGAAGGCAGGTTCGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDAGAGTTTGATCCTGGCTCAGGACGAACGCTGGCGGCGCGCCTAACACATGCAAGTCG No. 15AACGAGAGAGAGGGAGCTTGCTTCCTTGATCGAGTGGCGAACGGGTGAGTAACGCGTGAGGAACCTGCCTCAAAGAGGGGGACAACAGTTGGAAACGACTGCTAATACCGCATAAGCCCACGACCCGGCATCGGGAAGAGGGAAAAGGAGCAATCCGCTTTGAGATGGCCTCGCGTCCGATTAGCTAGTTGGTGAGGTAACGGCCCACCAAGCGACGATCGGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGTGGAGGAAGAAGGTCTTCGGATTGTAAACTCCTGTTGTTGAGGAAGATAATGACGGTACTCAACAAGGAAGTGACGGCTAACTACGTGCCAGCAGCCGCGGTAAAACGTAGGTCACAAGCGTTGTCCGGAATTACTGGGTGTAAAGGGAGCGCAGGCGGGCGATCAAGTTGGAAGTGAAATCCATGGGCTCAACCCATGAACTGCTTTCAAAACTGGTCGTCTTGAGTAGTGCAGAGGTAGGCGGAATTCCCGGTGTAGCGGTGGAATGCGTAGATATCGGGAGGAACACCAGTGGCGAAGGCGGCCTACTGGGCACCAACTGACGCTGAGGCTCGAAAGTGTGGGTAGCAAACAGGATTAGATACCCTGGTAGTCCACACCGTAAACGATGATTACTAGGTGTTGGGAGATTGACCCTCTCAGTGCCGCAGTTAACACAATAAGTAATCCACCTGGGGAGTACGACCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGTGGAGTATGTGGTTTAATTCGACGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCTTGACGATGCTGGAAACAGTATTTCTCTTCGGAGCAAGGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATGGTCAGTTACTACGCAAGAGGACTCTGGCCAGACTGCCGTTGACAAAACGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCTTTATGACTTGGGCTACACACGTACTACAATGGCGTTAAACAAAGAGAAGCAAGACCGCGAGGTGGAGCAAAACTCAGAAACAACGTCCCAGTTCGGACTGCAGGCTGCAACTCGCCTGCACGAAGTCGGAATTGCTAGTAATCGTGGATCAGCATGCCACGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGAGAGCCGGGGGGACCCGAAGTCGGTAGTCTAACCGCAAGGAGGACGCCGCCGAAGGTAAAACTGGTGATTGGGGTGAAGTCGTAACAAGGTAGCCGT SEQ IDATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGGCAGGCTTAACACATGCAA No. 16GTCGAGGGGCAGCATAATGGTAGTAATACTATTGATGGCGACCGGCGGACGGGTGCGTAACGCGTATGCAACCTACCCTTTACAGGGGGATAACACTGAGAAATCGGTACTAATACCCCATAATATTCTGGGAGGCATCTTTCGGAGTTGAAAGCTTTGGTGGTAAAGGATGGGCATGCGTTGTATTAGCTAGTTGGTAAGGTAACGGCTTACCAAGGCGACGATACATAGGGGGACTGAGAGGTTAACCCCCCACATTGGTACTGAGACACGGACCAAACTCCTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGACGGAAGTCTGAACCAGCCATGCCGCGTGCAGGAAGACGGCTCTATGAGTTGTAAACTGCTTTTGTACGAGGGTAAACGCAGATACGTGTATCTGCCTGAAAGTATCGTACGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCAAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGTAGGCGGTTTAGTAAGTCAGCGGTGAAATTTTGGTGCTTAACACCAAACGTGCCGTTGATACTGCTGGGCTAGAGAGTAGTTGCGGTAGGCGGAATGTATGGTGTAGCGGTGAAATGCTTAGAGATCATACAGAACACCGATTGCGAAGGCAGCTTACCAAACTATATCTGACGTTGAGGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCAGTAAACGATGATAGCTCGTTGTCGGCGATACACAGTCGGTGACTAAGAGAAATCGATAAGCTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCGGGCTTGAAAGTTACTGACGATTCTGGAAACAGGATTTCCCTTCGGGGCAGGAAACTAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAACGAGCGCAACCCCTACTGATAGTTGCCATCAGAGCGTTTGAGCGATCAAACAAGCTGGGCACTCTATCGGGACTGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGTAGGTACAGAGGGCAGCCACCCAGTGATGGGGAGCGAATCTCGAAAGCCTATCTCAGTTCGGATTGGAGGCTGAAACTCGCCTCCATGAAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGGAGTTGGGGGTGCCTGAAGTTCGTGACCGAAAGGAGCGACCTAGGGCAAAACCGATGACTGGGGCTAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ IDTTTAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 17GTCGAACGGAGTTATTTTGGAAATCTCTTCGGAGATGGAATTCATAACTTAGTGGCGGACGGGTGAGTAACGCGTGAGCAATCTGCCCTTAGGTGGGGGATAACAGCCGGAAACGGCTGCTAATACCGCATAACACATTGAAGCCGCATGGTTTTGATGTCAAAGATTTATTGCCTTTGGATGAGCTCGCGTCTGATTAGCTGGTTGGCGGGGTAACGGCCCACCAAGGCGACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCAACGCCGCGTGATTGAAGAAGGCCTTCGGGTTGTAAAGATCTTTAATTGGGGACGAAAAATGACGGTACCCAAAGAATAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGCGAGTAGGCGGGCTGGCAAGTTGGGAGTGAAATCCCGGGGCTTAACCCCGGAACTGCTTTCAAAACTGCTGGTOTTGAGTGATGGAGAGGCAGGCGGAATTCCGTGTGTAGCGGTGAAATGCGTAGATATACGGAGGAACACCAGTGGCGAAGGCGGCCTGCTGGACATTAACTGACGCTGAGGAGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGGATACTAGGTGTGGGAGGTATTGACCCCTTCCGTGCCGGAGTTAACACAATAAGTATCCCACCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTCTTGACATCCCTCTGACCGCCCTAGAGATAGGGTTTCCCTTCGGGGCAGAGGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTACGGTTAGTTGATACGCAAGATCACTCTAGCCGGACTGCCGTTGACAAAACGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTACTACAATGGCAGTCATACAGAGGGAAGCAAAACAGTGATGTGGAGCAAATCCCTAAAAGCTGTCCCAGTTCAGATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGAATTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGAGAGCCGGTAATACCCGAAGTCCGTAGCCTAACCGCAAGGAGGGCGCGGCCGAAGGTAGGACTGGTAATTAGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDACGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 18GTCGAACGGTTAAGGCGCCTTCGGGCGCGAATAGAGTGGCGAACGGGTGAGTAACACGTGACCAACCTGCCCCCCTCCCCGGGATAACGCGAGGAAACCCGCGCTAATACCGGATACTCCGCCCCTCCCGCATGGGAGGGGCGGGAAAGCCCCGACGGAGGGGGATGGGGTCGCGGCCCATTAGGTAGACGGCGAGGCAACGGCCCACCGTGCCTGCGATGGGTAGCCGGGTTGAGAGACCGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGCGCAATGGGGGGAACCCTGACGCAGCAACGCCGCGTGCGGGACGAAGGCCTTCGGGTTGTAAACCGCTTTCAGCAGGGAAGAAGTTGACGGTACCTGCAGAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCGAGCGTTATCCGGATTCATTGGGCGTAAAGCGCGCGTAGGCGGCCCGTCAAGeGGAACCTCTAACCCGAGGGCTCAACCCCCGGCCGGGTTCCGAACTGGCAGGCTCGAGTTTGGTAGAGGAAGATGGAATTCCCGGTGTAGCGGTGGAATGCGCAGATATCGGGAAGAACACCGATGGCGAAGGCAGTCTTCTGGGCCATCAACTGACGCTGAGGCGCGAAAGCTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCCAGCCGTAAACGATGGGTGCTAGGTGTGGGGGGATCATCCCTCCGTGCCGCAGCCAACGCATTAAGCACCCCGCCTGGGGAGTACGGCCGCAAGGCTAAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGCGGAGCATGTGGCTTAATTCGAAGCAACGCGAAGAACCTTACCAGGGCTTGACATGCTGGTGAAGCCGGGGAAACCCGGTGGCCGAGAGGAGCCAGCGCAGGTGGTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGCCATATGTTGCCAGCATTCAGTTGGGGACTCATATGGGACTGCCGGCGTCAAGCCGGAGGAAGGTGGGGACGACGTCAAGTCATCATGCCCTTTATGCCCTGGGCTGCACACGTGCTACAATGGCCGGTACAACGGGCCGCGACCTGGCGACAGGAAGCGAATCCCTCAAAGCCGGCCCCAGTTCGGATCGGAGGCTGCAACCCGCCTCCGTGAAGTCGGAGTTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACCCGAGTCGTCTGCACCCGAAGCCGCCGGCCGAACCCGCAAGGGGCGGAGGCGTCGAAGGTGTGGAGGGTAAGGGGGGTGAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 19GTCGAGCGAAGCACTTGCCATTGACTCTTCGGAAGATTTGGCATTTGACTGAGCGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGAATAACAGTTAGAAATGGCTGCTAATGCCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTGAGGTGGTATGAGATGGGCCCGCGTCTGATTAGGTAGTTGGCGGGGTAACGGCCCACCAAGCCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTGATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGGGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGGACGGGCAAGTCTGATGTGAAAGCCCGGGGCTTAACCCCGGGACTGCATTGGAAACTGTCCATCTTGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGTTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGTTGCAAAGCAATCCGGTGCCGCAGCAAACGCAGTAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCTGCCTGACCGTTCCTTAACCGGAACTTTCCTTCGGGACAGGCAAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGTCCTTAGTAGCCAGCAGTCCGGCTGGGCACTCTAGGGAGACTGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGTGGTGACACTGAGCAAATCTCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCACGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCTAACCGCAAGGGAGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTTATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 20GTCGAACGAAGCATTTAAGACGGATTCTTTCGGGATGAAGACTTTTATGACTGAGTGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCACACAGGGGGATAGCAGTTGGAAACGGCTGATAATACCGCATAAGCGCACAGTACCGCATGGTACAGTGTGAAAAACTCCGGTGGTGTGAGATGGACCCGCGTCTGATTAGCTTGTTGGCAGGGTAACGGCCTACCAAGGCAACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTGATGCAGCGACGCCGCGTGAGTGAAGAAGTAATTCGTTATGTAAAGCTCTATCAGCAGGGAAGATAGTGACGGTACCTGACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGGTGGCATCACAAGTCAGAAGTGAAAGCCCGGGGCTCAACCCCGGGACTGCTTTTGAAACTGTGGAGCTGGAGTGCAGGAGAGGCAAGTGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTGCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGGCTCATAAGAGCTICGGTGCCGCAGCAAACGCAATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAG,A.ACCTTACCAAGTCTTGACATCCTCTTGCCCGGTCAGTAATGTGACCTTTTCTTCGGAACAAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTATTCTTAGTAGCCAGCATATAAGGTGGGCACTCTAGGAAGACTGCCAGGGATAACCTGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGTGAAGCGAGAGTGTGAGCTTAAGCAAATCACAAAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCGGAAATGCCCGAAGTCGGTGACCTAACGAAAGAAGGAGCCGCCGAAGGCAGGTCTGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAAGT NO. 21CGAACGGAGTTATGCAGAGGAAGTTTTCGGATGGAATCGGCGTAACTTAGTGGCGGACGGGTGAGTAACGCGTGGGAAACCTGCCCTGTACCGGGGGATAACACTTAGAAATAGGTGCTAATACCGCATAAGCGCACAGCTTCACATGARGCAGTGTGAAAAACTCCGGTGGTACAGGATGGTCCCGCGTCTGATTAGCCAGTTGGCAGGGTAAYGGCCTACCAAAGCGACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGTGAGTGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGGGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGGCATGACAAGCCAGATGTGAAAACCCAGGGCTCAACCCTGGGACTGCATTTGGAACTGCCAGGCTGGAGTGCAGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACTGTAACTGACGTTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCGGTAAACGATGATTGCTAGGTGTAGGTGGGTATGGACCCATCGGTGCCGCAGCTAACGCAATAAGCAATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCAATGACGTGTCCGTAACGGGGCATTCTCTTCGGAGCATTGGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATCCTTAGTAGCCAGCAGGTARAGCTGGGCACTCTAGGGAGACTGCCGGGGATAACCCGGAGGAAGGCGGGGAYGACGTCAAATCATCATGCCCCTTATGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGTGATGTTGAGCAAATCCCAGAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGAAGCTGGAATCGCTAGTAATCGCGAATCAGCATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGCCTGTGACCTAACCGCAAGGGAGGAGCAGTCGAAGGCAGGTCTAATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTTTAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA NO. 22GTCGAACGGAGTTATTTTGGAAATCTCTTCGGGGATGGAATTCATAACTTAGTGGCGGACGGGTGAGTAACGCGTGAGCAATCTGCCCTTAGGTGGGGGATAACAGCCGGAAACGGCTGCTAATACCGCATAACACATTGAAGCCGCATGGTTTTGATGTCAAAGATTTATTGCCTTTGGATGAGCTCGCGTCTGATTAGCTGGTTGGCGGGGTAACGGCCCACCAAGGCGACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCAACGCCGCGTGATTGAAGAAGGCCTTCGGGTTGTAAAGATCTTTAATTGGGGACGAAWWWTGACGGTACCCAAAGAATAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGCGAGTAGGCGGGCTGGCAAGTTGGGAGTGAAATCCCGGGGCTTAACCCCGGAACTGCTTTCAAAACTGCTGGTCTTGAGTGATGGAGAGGCAGGCGGAATTCCGTGTGTAGCGGTGAAATGCGTAGATATACGGAGGAACACCAGTGGCGAAGGCGGCCTGCTGGACATTAACTGACGCTGAGGAGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGGATACTAGGTGTGGGAGGTATTGACCCCTTCCGTGCCGGAGTTAACACAATAAGTATCCCACCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGIGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTOTTGACATCCCTCTGACCGCCCTAGAGATAGGGTTTCCCTTCGGGGCAGAGGTGACAGGTGGTGCATGGITGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTACGGTTAGTTGATACGAAAGATCACTCTAGCCGGACTGCCGTTGACAAAACGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTACTACAATGGCAGTCATACAGAGGGAAGCAAAACAGTGATGTGGAGCAAATCCCTAAAAGCTGTCCCAGTTCAGATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGAATTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGAGAGCCGGTAATACCCGAAGTCCGTAGCCTAACCGCAAGGAGGGCGCGGCCGAAGGTAGGACTGGTAATTAGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDACGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA NO. 23GTCGAACGGTTAAGGCGCCTTCGGGCGCGAATAGAGTGGCGAACGGGTGAGTAACACGTGACCAACCTGCCCCCCTCCCCGGGATAACGCGAGGAAACCCGCGCTAATACCGGATACTCCGCCCCTCCCGCATGGGAGGGGCGGGAAAGCCCCGACGGAGGGGGATGGGGTCGCGGCCCATTAGGTAGACGGCGGGGCAACGGCCCACCGTGCCTGCGATGGGTAGCCGGGTTGAGAGACCGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGCGCAATGGGGGGAACCCTGACGCAGCAACGCCGCGTGCGGGACGAAGGCCTTCGGGTTGTAAACCGCTTTCAGCAGGGAAGAAGTTGACGGTACCTGCAGAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCGAGCGTTATCCGGATTCATTGGGCGTAAAGCGCGCGTAGGCGGCCCGTCAAGCGGAACCTCTAACCCGAGGGCTCAACCCCCGGCCGGGTTCCGAACTGGCAGGCTCGAGTTTGGTAGAGGAAGATGGAATTCCCGGTGTAGCGGTGGAATGCGCAGATATCGGGAAGAACACCGATGGCGAAGGCAGTCTTCTGGGCCATCAACTGACGCTGAGGCGCGAAAGCTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCCAGCCGTAAACGATGGGYGCTAGGTGTGGGGGGATCATCCCTCCGTGCCGCAGCCAACGCATTAAGCRCCCCGCCTGGGGAGTACGGCCGCAAGGCTAAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGCGGAGCATGTGGCTTAATTCGAAGCAACGCGAAGAACCTTACCAGGGCTTGACATGCTGGTGAAGCCGGGGAAACCCGGTGGCCGAGAGGAGCCAGCGCAGGTGGTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGCCATATGTTGCCAGCATTCAGTTGGGGACTCATATGGGACTGCCGGCGTCAAGCCGGAGGAAGGTGGGGACGACGTCAAGTCATCATGCCCTTTATGCCCTGGGCTGCACACGTGCTACAATGGCCGGTACAACGGGCCGCGACCTGGCGACAGGAAGCGAATCCCTCAAAGCCGGCCCCAGTTCGGATCGGAGGCTGCAACCCGCCTCCGTGAAGTCGGAGTTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACCCGAGTCGTCTGCACCCGAAGCCGCCGGCCGAACCCGCAAGGGGCGGAGGCGTCGAAGGTGTGGAGGGTAAGGGGGGTGAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCATGCCTAATACATGCAAG NO. 24TCGAACGAAGTOTTTAGGAAGCTTGCTTCCAAAGAGACTTAGTGGCGAACGGGTGAGTAACACGTAGGTAACCTGCCCATGTGCCCGGGATAACTGCTGGAAACGGTAGCTAAAACCGGATAGGTATGAGGGAGGCATCTTCCTCATATTAAAGCACCTTCGGGTGTGAACATGGATGGACCTGCGGCGCATTAGCTGGTTGGTGAGGTAACGGCCCACCAAGGCGATGATGCGTAGCCGACCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAAACTCCTACGGGAGGCAGCAGTAGGGAATTTTCGTCAATGGGGGGAACCCTGAACGAGCAATGCCGCGTGTGTGAAGAAGGTOTTCGGATCGTAAAGCACTGTTGTAAGTGAAGAATGCCATATAGAGGAAATGCTATGTGGGTGACGGTAGCTTACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATCATTGGGCGTAAAGGGTGCGTAGGTGGCACGATAAGTCTGAAGTAAAAGGCAACAGCTCAACTGTTGTATGCTTTGGAAACTGTCGAGCTAGAGTGCAGAAGAGGGCGATGGAATTCCATGTGTAGCGGTAAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGTCGCCTGGTCTGTAACTGACACTGATGCACGAAAGCGTGGGGAGCAAATAGGATTAGATACCCTAGTAGTCCACGCCGTAAACGATGAGAACTAAGTGTTGGAGAGATTCAGTGCTGCAGTTAACGCAATAAGTTCTCCGCCTGGGGAGTATGCACGCAAGTGTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGCCTTGACATGGATATAAATGTTCTAGAGATAGAAAGATAGCTATATATCACACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCTTCTGTTACCAGCATTAAGTTGGGGACTCAGGAGAGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGGCCTGGGCTACACACGTACTACAATGGCGCCTACAAAGAGCAGCGACACCGCGAGGTGGAGCGAATCTCATAAAGGGCGTCTCAGTTCGGATTGAAGTCTGCAACTCGACTTCATGAAGTCGGAATCGCTAGTAATCGCAGATCAGCATGCTGCGGTGAATACGTTCTCGGGCCTTGTACACACCGCCCGTCAAACCATGGGAGTTGGTAATACCCGAAGCCGGTGGCATAACCGCAAGGAGTGAGCCGTCGAAGGTAGGACCGATGACTGGGGTTAAGTCGTAACAAGGTATCCCTACGGGAACGTGGGGATGGATCACCTCCTTT SEQ IDTCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA NO. 25GTCGAGCGAAGCRCTTRARYGGATCTCTTCGGATTGAARYTTWTKTGACTGAGCGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTAGAAATGGCTGCTAATACCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTCCGGTGGTATGAGATGGACCCGCGTCTGATTAGCTAGTTGGAGGGGTAACGGCCCACCAAGGCGACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGGGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGGAAGAGCAAGTCTGATGTGAAAGGCTGGGGCTTAACCCCAGGACTGCATTGGAAACTGTTTTTCTAGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGTTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGTGGCAAAGCCATTCGGTGCCGCAGCAAACGCAATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCTCTGACCGGCCCGTAACGGGGCCTTCCCTTCGGGGCAGAGGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTATCCTTAGTAGCCAGCAGGTRRAGCTGGGCACTCTAGGGAGACTGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGCGATGTTGAGCAAATCCCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCACGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCCAACCTTAYAGGAGGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDCGAAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGACAGGCCTAACACATGCAAGT NO. 26CGAGGGGCAGCGGRGAGGYAGCAATACCTTTGCCGGCGACCGGCGCACGGGTGAGTAACACGTATGCAATCCACCTGTAACAGGGGGATAACCCGGAGAAATCCGGACTAATACCCCATAATATGGGCGCTCCGCATGGAGRGTCCATTAAAGAGAGCAATTTTGGTTACAGACGAGCATGCGCTCCATTAGCCAGTTGGCGGGGTAACGGCCCACCAAAGCGACGATGGATAGGGGTTCTGAGAGGAAGGTCCCCCACATTGGAACTGAGACACGGTCCAAACTCCTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGTCGGCAGACTGAACCAGCCAAGTCGCGTGAGGGAAGACGGCCCTACGGGTTGTAAACCTCTTTTGTCGGAGAGTAAAGTRCGCTACGTGTAGYGTATTGCAAGTATCCGAAGAAAAAGCATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATGCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGTAGGCGGCACGCCAAGTCAGCGGTGAAATTTCCGGGCTCAACCCGGACTGTGCCGTTGAAACTGGCGAGCTAGAGTGCACAAGAGGCAGGCGGAATGCGTGGTGTAGCGGTGAAATGCATAGATATCACGCAGAACCCCGATTGCGAAGGCAGCCTGCTAGGGTGCGACAGACGCTGAGGCACGAAAGCGTGGGTATCGAACAGGATTAGATACCCTGGTAGTCCACGCAGTAAACGATGAATACTAACTGTTTGCGATACAATGTAAGCGGTACAGCGAAAGCGTTAAGTATTCCACCTGGGGAGTACGCCGGCAACGGTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCGGGCTCAAACGCAGGGGGAATGCCGGTGAAAGTCGGCAGCTAGCAATAGTCACCTGCGAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGCTTAAGTGCCATAACGAGCGCAACCCCTATGGACAGTTACTAACGGGTGAAGCCGAGGACTCTGTCTAGACTGCCGGCGCAAGCCGCGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGCAGGTACAGAAGGCAGCCAGTCAGCAATGACGCGCGAATCCCGAAAACCTGTCTCAGTTCGGATTGGAGTCTGCAACCCGACTCCATGAAGCTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGAAGCCGGGAGTACCTGAAGCATGCAACCGCAAGGAGCGTACGAAGGTAATACCGGTAACTGGGGCTAAGTCGTAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ IDTCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA NO. 27GTCGAGCGAAGCACTTRYYATTGAMTCTTCGGARGATTTRGCATKTGACTGAGCGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGAATAACAGTTAGAAATGGCTGCTAATGCCGCATAAGCGCACAGGRCCGCATGGTCYGGTGTGAAAAACTSMGGTGGTATGAGATGGROCCGCGTCTGATTAGGTAGTTGGCGGGGTAACGGCCCACCAAGCCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTGATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGGGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGGACGGGCAAGTCTGATGTGAAAGCCCGGGGCTTAACCCCGGGACTGCATTGGAAACTGTCCATCTTGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGTTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGTTGCAAAGCAATCCGGTGCCGCAGCAAACGCAGTAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCTGCCTGACCGTTCCTTAACCGGAACTTTCCTTCGGGACAGGCAAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGTCCTTAGTAGCCAGCAGTCCGGCTGGGCACTCTAGGGAGACTGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGTGGTGACACTGAGCAAATCTCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCACGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCTAACCGCAAGGGAGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDTTATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA NO. 28GTCGAACGAAGCATTTGMGACRGATTYYTTCGGRWTGAAGACTTTTATGACTGAGTGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCACACAGGGGGATAGCAGTTGGAAACGGCTGATAATACCGCATAAGCGCACAGTACCGCATGGTACAGTGTGAAAAACTCCGGTGGTGTGAGATGGACCCGCGTCTGATTAGCTTGTTGGCRGGGTAACGGCCYACCAAGGCAACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTGATGCAGCGACGCCGCGTGAGTGAAGAAGTAATTCGTTATGTAAAGCTCTATCAGCAGGGAAGATAGTGACGGTACCTGACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGGTGGCATCACAAGTCAGAAGTGAAAGCCCGGGGCTCAACCCCGGGACTGCTTTTGAAACTGTGGAGCTGGAGTGCAGGAGAGGCAAGTGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTGCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGGCTCATAAGAGCTTCGGTGCCGCAGCAAACGCAATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCTCTTGRCCGGTCAGTAATGTGRYCTTTTCTTCGGAACAAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTATTCTTAGTAGCCAGCATTTAAGRTGGGCACTCTAGGAAGACTGCCAGGGATAACCTGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGTGAAGCGAGAGTGTGAGCTTAAGCAAATCACAAAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTCGGAAATGCCCGAAGTCGGTGACCTAACGAAAGAAGGAGCCGCCGAAGGCAGGTCTGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ IDATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAAGT NO. 29CGAACGAAGCACTCTATTTGATTTTCTTCGGRAATGAAGATTTTGTGACTGAGTGGCGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTGGAAACGACTGCTAATACCGCATAAGCGCACAGGATYGCATGRTCCGGTGTGAAAAACTCCGGTGGTATGRGATGGACCCGCGTCTGATTAGCCAGTTGGCAGGGTAACGGCCTACCAAAGCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGCCCAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGGGAAGAAGAATGACGGTACCTGACTAAGAAGCACCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGTGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGCAGGCGGTGCGGCAAGTCTGATGTGAAAGCCCGGGGCTCAACCCCGGTACTGCATTGGAAACTGTCGTACTAGAGTGTCGGAGGGGTAAGTGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGATAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAATACTAGGTGTCGGGGAGCATTGCTCTTCGGTGCCGCAGCAAACGCAATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCGATGACAGAGTATGTAATGTASYYTCYCTTCGGRGCATCGGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGTYCTTAGTAGCCAGCGGTTCGGCCGGGCACTCTAGGGAGACTGCCAGGGATAACCTGGAGGAAGGCGGGGATGACGTCAAATCATCATGCCCCTTATGACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCRRAGCCGTGAGGCCGAGCAAATCTCAAAAATAACGTCTCAGTTCGGACTGTAGTCTGCAACCCGACTACACGAAGCTGGAATCGCTAGTAATCGCAGATCAGAATGCTGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGTCAGTGACCCAACCGCAAGGAGGGAGCTGCCGAAGGCAGGTTCGATAACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT

TABLE 3 16S rDNA sequence Consortium No Taxonomy identifier 1 2 3 4 5 67 8 9 10 B1 Eisenbergiella sp. SEQ ID No. 1 X X X X X X X X X X B2Butyricicoccus sp. SEQ ID No. 2 X X X X X X X X X B3 Clostridiales sp.SEQ ID No. 3 X X X X X B4 Alistipes obesi SEQ ID No. 4 X X B5 Alistipesindistinctus SEQ ID No. 5 X X X B6 Gordonibacter SEQ ID No. 6 X X X Xurolithinfaciens B7 Faecalitalea sp. SEQ ID No. 7 X X X X X X X X X B8Blautia sp. SEQ ID No. 8 X X X X X B9 Barnesiella SEQ ID No. 9 X X X X XX X intestinihominis B10 Alistipes timonensis SEQ ID No. 10 X X B11Blautia sp. SEQ ID No. 11 X X X X B12 Lachnospira sp. SEQ ID No. 12 X XB13 Ruminococcus callidus SEQ ID No. 13 X X X X X B14 Roseburia faecisSEQ ID No. 14 X X X X B15 Faecaiibacterium SEQ ID No. 15 X X prausnitziiB4 Alistipes obesi SEQ ID No. 16 X X B2 Butyricicoccus sp. SEQ ID No. 17X B6 Gordonibaoter SEQ ID No. 18 X X X urolithinfaciens B11 Blautia sp.SEQ ID No. 19 X X B12 Lachnospira sp. SEQ ID No. 20 X X Number ofbacteria 15 9 12 9 9 9 6 3 2 9

1. A method for treating cancer in a subject in need thereof, comprisingadministering a composition comprising isolated bacteria selected fromat least two species wherein the bacteria from the first speciescomprise a 16S rDNA sequence having at least 98.7% sequence identitywith a nucleic acid sequence according to SEQ ID NO: 1, and the bacteriafrom the second species comprise a 16S rDNA sequence having at least98.7% sequence identity with a nucleic acid sequence according to SEQ IDNO: 2 wherein said subject is receiving, has received or will receivetherapy with an immune checkpoint inhibitor, thereby treating thecancer.
 2. The method according to claim 1, wherein said compositionfurther comprises one or more bacteria comprising a 16S rDNA sequenceselected from SEQ ID NOs: 3 to 15 or a sequence having at least 98.7%sequence identity thereto.
 3. The method according to claim 1, whereinsaid composition further comprises bacteria from 7 different bacterialspecies wherein said bacteria comprise a 16S rDNA sequence selected fromSEQ ID NO: 3 to 15 or a sequence having at least 98.7% sequence identitythereto.
 4. The method according to claim 1, wherein said compositionfurther comprises bacteria from 4 different bacterial species whereinsaid bacteria comprise a 16S rDNA sequence selected from SEQ ID NO: 3 to15 or a sequence having at least 98.7% sequence identity thereto.
 5. Themethod according to claim 1, wherein the cancer is selected frommelanoma, bone cancer, pancreatic cancer, skin cancer, cancer of thehead or neck, uterine cancer, ovarian cancer, rectal cancer, cancer ofthe anal region, stomach cancer, testicular cancer, breast cancer, braincancer, carcinoma of the fallopian tubes, carcinoma of the endometrium,carcinoma of the cervix, carcinoma of the vagina, carcinoma of thevulva, cancer of the esophagus, cancer of the small intestine, cancer ofthe endocrine system, cancer of the thyroid gland, cancer of theparathyroid gland, cancer of the adrenal gland, kidney cancer, sarcomaof soft tissue, cancer of the urethra, cancer of the bladder, renalcancer, lung cancer, non-small cell lung cancer, thymoma, urothelialcarcinoma leukemia, prostate cancer, mesothelioma, adrenocorticalcarcinoma, lymphomas, gastric cancer, and multiple myelomas.
 6. Themethod according to claim 5, wherein the melanoma is Harding-Passeymelanoma, juvenile melanoma, lentigo maligna melanoma, malignantmelanoma, acral-lentiginous melanoma, amelanotic melanoma, benignjuvenile melanoma, Cloudman's melanoma, S91 melanoma, nodular melanoma,subungual melanoma, cutaneous melanoma, uveal/intraocular melanoma,superficial spreading melanoma, or cutaneous or intraocular malignantmelanoma.
 7. The method according to claim 1, wherein the immunecheckpoint inhibitor inhibits PD-1, PD-L1, TIM-3 or CTLA-4 activity. 8.The method according to claim 1, wherein the immune checkpoint inhibitoris an anti PD-1, PD-L1, TIM-3 or CTLA-4 antibody.
 9. The methodaccording to claim 1, wherein the immune checkpoint inhibitor isselected from nivolumab, pembrolizumab, cemiplimab, avelumab,durvalumab, atezolizumab, Spartalizumab, Camrelizumab, Sintilimab,Tislelizumab, Pidilizumab, Toripalimab, Ipilimumab or Tremelimumab. 10.The method according to claim 1, wherein the immune checkpoint inhibitoris an interfering nucleic acid molecule, a small molecule or aPROteolysis TArgeting Chimera (PROTAC).
 11. The method according toclaim 1, wherein the composition is administered by oral administrationor rectal administration.
 12. The method according to claim 1, whereinthe composition is in the form of a capsule, tablet, gel or liquid. 13.The method according to claim 1, wherein the subject has received prioranti-cancer therapy with an immune checkpoint inhibitor.
 14. The methodaccording to claim 1, wherein the immune checkpoint inhibitor isadministered before, after or at the same time as the bacterialcomposition.
 15. The method according to claim 1, wherein thecomposition comprises live, attenuated or killed bacteria.
 16. Themethod according to claim 1, wherein the composition is lyophilised. 17.The method according to claim 1, wherein the composition does notcomprise bacterial spores.
 18. The method according to claim 1, furthercomprising surgical, radiation, and/or chemotherapeutic cancerintervention or administration of a second anti-cancer therapeutic. 19.The method according to claim 1, wherein the subject has been determinedto be a non-responder to the previous anti-cancer treatment with acheckpoint inhibitor.
 20. The method according to claim 1, wherein thesubject has been determined to have a microbial profile in the gutmicrobiome with a low abundance of one or more bacteria comprising a 16SrDNA sequence selected from SEQ ID NOs: 1 to 15 or a sequence having atleast 98.7% sequence identity thereto compared to a reference value.